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

Non-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no prior comprehensive, head-to-head accuracy comparison of the various tools has been published. Here, we compared the outcome accuracies obtained for clinically validated samples with five commonly used computational NIPT aneuploidy analysis tools (WisecondorX, NIPTeR, NIPTmer, RAPIDR, and GIPseq) across various sequencing depths (coverage) and fetal DNA fractions. The sample set included cases of fetal trisomy 21 (Down syndrome), trisomy 18 (Edwards syndrome), and trisomy 13 (Patau syndrome). We determined that all of the compared tools were considerably affected by lower sequencing depths, such that increasing proportions of undetected trisomy cases (false negatives) were observed as the sequencing depth decreased. We summarised our benchmarking results and highlighted the advantages and disadvantages of each computational NIPT software. To conclude, trisomy detection for lower coverage NIPT samples (e.g. 2.5M reads per sample) is technically possible but can, with some NIPT tools, produce troubling rates of inaccurate trisomy detection, especially in low-FF samples. Author summaryNon-invasive prenatal testing analysis relies on computational algorithms that are used for inferring chromosomal aneuploidies, such as chromosome 21 triploidy in the case of Down syndrome. However, the performance of these algorithms has not been compared on the same clinically validated data. Here we conducted a head-to-head comparison of WGS-based NIPT aneuploidy detection tools. Our findings indicate that at and below 2.5M reads per sample, the least accurate algorithm would miss detection of almost a third of trisomy cases. Furthermore, we describe and quantify a previously undocumented aneuploidy risk uncertainty that is mainly relevant in cases of very low sequencing coverage (at and below 1.25M reads per sample) and could, in the worst-case scenario, lead to a false negative rate of 245 undetected trisomies per 1,000 trisomy cases. Our findings underscore the importance of the informed selection of NIPT software tools in combination with sequencing coverage, which directly impacts NIPT sequencing cost and accuracy.Peer reviewe

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

Non-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no prior comprehensive, head-to-head accuracy comparison of the various tools has been published. Here, we compared the outcome accuracies obtained for clinically validated samples with five commonly used computational NIPT aneuploidy analysis tools (WisecondorX, NIPTeR, NIPTmer, RAPIDR, and GIPseq) across various sequencing depths (coverage) and fetal DNA fractions. The sample set included cases of fetal trisomy 21 (Down syndrome), trisomy 18 (Edwards syndrome), and trisomy 13 (Patau syndrome). We determined that all of the compared tools were considerably affected by lower sequencing depths, such that increasing proportions of undetected trisomy cases (false negatives) were observed as the sequencing depth decreased. We summarised our benchmarking results and highlighted the advantages and disadvantages of each computational NIPT software. To conclude, trisomy detection for lower coverage NIPT samples (e.g. 2.5M reads per sample) is technically possible but can, with some NIPT tools, produce troubling rates of inaccurate trisomy detection, especially in low-FF samples.Author summaryNon-invasive prenatal testing analysis relies on computational algorithms that are used for inferring chromosomal aneuploidies, such as chromosome 21 triploidy in the case of Down syndrome. However, the performance of these algorithms has not been compared on the same clinically validated data. Here we conducted a head-to-head comparison of WGS-based NIPT aneuploidy detection tools. Our findings indicate that at and below 2.5M reads per sample, the least accurate algorithm would miss detection of almost a third of trisomy cases. Furthermore, we describe and quantify a previously undocumented aneuploidy risk uncertainty that is mainly relevant in cases of very low sequencing coverage (at and below 1.25M reads per sample) and could, in the worst-case scenario, lead to a false negative rate of 245 undetected trisomies per 1,000 trisomy cases. Our findings underscore the importance of the informed selection of NIPT software tools in combination with sequencing coverage, which directly impacts NIPT sequencing cost and accuracy

Fetal sex determination in twin pregnancies using non-invasive prenatal testing

Non-invasive prenatal testing (NIPT) is accurate for fetal sex determination in singleton pregnancies, but its accuracy is not well established in twin pregnancies. Here, we present an accurate sex prediction model to discriminate fetal sex in both dichorionic diamniotic (DCDA) and monochorionic diamniotic/monochorionic monoamniotic (MCDA/MCMA) twin pregnancies. A retrospective analysis was performed using a total of 198 twin pregnancies with documented sex. The prediction was based on a multinomial logistic regression using the normalized frequency of X and Y chromosomes, and fetal fraction estimation. A second-step regression analysis was applied when one or both twins were predicted to be male. The model determines fetal sex with 100% sensitivity and specificity when both twins are female, and with 98% sensitivity and 95% specificity when a male is present. Since sex determination can be clinically important, implementing fetal sex determination in twins will improve overall twin pregnancies management

Fetal sex determination in twin pregnancies using non-invasive prenatal testing

Non-invasive prenatal testing (NIPT) is accurate for fetal sex determination in singleton pregnancies, but its accuracy is not well established in twin pregnancies. Here, we present an accurate sex prediction model to discriminate fetal sex in both dichorionic diamniotic (DCDA) and monochorionic diamniotic/monochorionic monoamniotic (MCDA/MCMA) twin pregnancies. A retrospective analysis was performed using a total of 198 twin pregnancies with documented sex. The prediction was based on a multinomial logistic regression using the normalized frequency of X and Y chromosomes, and fetal fraction estimation. A second-step regression analysis was applied when one or both twins were predicted to be male. The model determines fetal sex with 100% sensitivity and specificity when both twins are female, and with 98% sensitivity and 95% specificity when a male is present. Since sex determination can be clinically important, implementing fetal sex determination in twins will improve overall twin pregnancies management

Predicting fetoplacental chromosomal mosaicism during non-invasive prenatal testing

ObjectiveNon-invasive prenatal detection of aneuploidies can be achieved with high accuracy through sequencing of cell-free maternal plasma DNA in the maternal blood plasma. However, false positive and negative non-invasive prenatal testing (NIPT) results remain. Fetoplacental mosaicism is the main cause for false positive and false negative NIPT. We set out to develop a method to detect placental chromosomal mosaicism via genome-wide circulating cell-free maternal plasma DNA screening.MethodAneuploidy detection was combined with fetal fraction determination to enable the detection of placental mosaicism. This pipeline was applied to whole genome sequencing data derived from 19735 plasma samples. Following an abnormal NIPT, test results were validated by conventional invasive prenatal or postnatal genetic testing.ResultsRespectively 3.2% (5/154), 12.8% (5/39), and 13.3% (2/15) of trisomies 21, 18, and 13 were predicted and confirmed to be mosaic. The incidence of other, rare autosomal trisomies was similar to 0.3% (58/19,735), 45 of which were predicted to be mosaic. Twin pregnancies with discordant fetal genotypes were predicted and confirmed.ConclusionThis approach permits the non-invasive detection of fetal autosomal aneuploidies and identifies pregnancies with a high risk of fetoplacental mosaicism. Knowledge about the presence of chromosomal mosaicism in the placenta influences risk estimation, genetic counseling, and improves prenatal management

Improving molecular diagnosis in epilepsy by a dedicated high-throughput sequencing platform

We analyzed by next-generation sequencing (NGS) 67 epilepsy genes in 19 patients with different types of either isolated or syndromic epileptic disorders and in 15 controls to investigate whether a quick and cheap molecular diagnosis could be provided. The average number of nonsynonymous and splice site mutations per subject was similar in the two cohorts indicating that, even with relatively small targeted platforms, finding the disease gene is not an univocal process. Our diagnostic yield was 47% with nine cases in which we identified a very likely causative mutation. In most of them no interpretation would have been possible in absence of detailed phenotype and familial information. Seven out of 19 patients had a phenotype suggesting the involvement of a specific gene. Disease-causing mutations were found in six of these cases. Among the remaining patients, we could find a probably causative mutation only in three. None of the genes affected in the latter cases had been suspected a priori. Our protocol requires 8-10 weeks including the investigation of the parents with a cost per patient comparable to sequencing of 1-2 medium-to-large-sized genes by conventional techniques. The platform we used, although providing much less information than whole-exome or whole-genome sequencing, has the advantage that can also be run on 'benchtop' sequencers combining rapid turnaround times with higher manageability

Noninvasive prenatal testing using a novel analysis pipeline to screen for all autosomal fetal aneuploidies improves pregnancy management

Noninvasive prenatal testing by massive parallel sequencing of maternal plasma DNA has rapidly been adopted as a mainstream method for detection of fetal trisomy 21, 18 and 13. Despite the relative high accuracy of current NIPT testing, a substantial number of false-positive and false-negative test results remain. Here, we present an analysis pipeline, which addresses some of the technical as well as the biologically derived causes of error. Most importantly, it differentiates high z-scores due to fetal trisomies from those due to local maternal CNVs causing false positives. This pipeline was retrospectively validated for trisomy 18 and 21 detection on 296 samples demonstrating a sensitivity and specificity of 100%, and applied prospectively to 1350 pregnant women in the clinical diagnostic setting with a result reported in 99.9% of cases. In addition, values indicative for trisomy were observed two times for chromosome 7 and once each for chromosomes 15 and 16, and once for a segmental trisomy 18. Two of the trisomies were confirmed to be mosaic, one of which contained a uniparental disomy cell line. As placental trisomies pose a risk for low-grade fetal mosaicism as well as uniparental disomy, genome-wide noninvasive aneuploidy detection is improving prenatal management