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.

Prenatal diagnosis of a 46,XY karyotype female fetus with an SRY-associated gonadal dysgenesis, conceived through an intracytoplasmic sperm injection: a case report.

BACKGROUND: Permanent progression of paternal age and development of reproductive medicine lead to increase in number of children conceived with assisted reproductive techniques (ART). Although it is uncertain if ARTs have direct influence on offspring health, advanced paternal age, associated comorbidities and reduced fertility possess significant risks of genetic disorders to the offspring. With a broad implementation of a non-invasive prenatal testing (NIPT), more cases of genetic disorders, including sex discordance are revealed. Among biological causes of sex discordance are disorders of sexual development, majority of which are associated with the SRY gene. CASE PRESENTATION: We report a case of a non-invasive prenatal testing and ultrasound sex discordance in a 46,XY karyotype female fetus with an SRY pathogenic variant, who was conceived through an intracytoplasmic sperm injection (ICSI) due to severe oligozoospermia of the father. Advanced mean age of ICSI patients is associated with risk of de novo mutations and monogenic disorders in the offspring. Additionally, ICSI patients have higher risk to harbour infertility-predisposing mutations, including mutations in the SRY gene. These familial and de novo genetic factors predispose ICSI-conceived children to congenital malformations and might negatively affect reproductive health of ICSI-patients' offspring. CONCLUSIONS: Oligozoospermic patients planning assisted reproduction are warranted to undergo genetic counselling and testing for possible inherited and mosaic mutations, and risk factors for de novo mutations.

Creating basis for introducing non-invasive prenatal testing in the Estonian public health setting.

OBJECTIVE: The study aimed to validate a whole-genome sequencing-based NIPT laboratory method and our recently developed NIPTmer aneuploidy detection software with the potential to integrate the pipeline into prenatal clinical care in Estonia. METHOD: In total, 424 maternal blood samples were included. Analysis pipeline involved cell-free DNA extraction, library preparation and massively parallel sequencing on Illumina platform. Aneuploidies were determined with NIPTmer software, which is based on counting pre-defined per-chromosome sets of unique k-mers from sequencing raw data. SeqFF was implemented to estimate cell-free fetal DNA (cffDNA) fraction. RESULTS: NIPTmer identified correctly all samples of non-mosaic trisomy 21 (T21, 15/15), T18 (9/9), T13 (4/4) and monosomy X (4/4) cases, with the 100% sensitivity. However, one mosaic T18 remained undetected. Six false-positive (FP) results were observed (FP rate of 1.5%, 6/398), including three for T18 (specificity 99.3%) and three for T13 (specificity 99.3%). The level of cffDNA of <4% was estimated in eight samples, including one sample with T13 and T18. Despite low cffDNA level, these two samples were determined as aneuploid. CONCLUSION: We believe that the developed NIPT method can successfully be used as a universal primary screening test in combination with ultrasound scan for the first trimester fetal examination.

Whole exome sequencing of benign pulmonary metastasizing leiomyoma reveals mutation in the BMP8B gene.

BACKGROUND: Benign metastasizing leiomyoma (BML) is an orphan neoplasm commonly characterized by pulmonary metastases consisting of smooth muscle cells. Patients with BML have usually a current or previous uterine leiomyoma, which is therefore suggested to be the most probable source of this tumour. The purpose of this case report was to determine the possible genetic grounds for pulmonary BML. CASE PRESENTATION: We present a case report in an asymptomatic 44-year-old female patient, who has developed uterine leiomyoma with subsequent pulmonary BML. Whole exome sequencing (WES) was used to detect somatic mutations in BML lesion. Somatic single nucleotide mutations were identified by comparing the WES data between the pulmonary metastasis and blood sample of the same BML patient. One heterozygous somatic mutation was selected for validation by Sanger sequencing. Clonality of the pulmonary metastasis and uterine leiomyoma was assessed by X-chromosome inactivation assay. CONCLUSIONS: We describe a potentially deleterious somatic heterozygous mutation in bone morphogenetic protein 8B (BMP8B) gene (c.1139A > G, Tyr380Cys) that was identified in the pulmonary metastasis and was absent from blood and uterine leiomyoma, and may play a facilitating role in the metastasizing of BML. The clonality assay confirmed a skewed pattern of X-chromosome inactivation, suggesting monoclonal origin of the pulmonary metastases.

Targeted gene expression profiling for accurate endometrial receptivity testing.

Expressional profiling of the endometrium enables the personalised timing of the window of implantation (WOI). This study presents and evaluates a novel analytical pipeline based on a TAC-seq (Targeted Allele Counting by sequencing) method for endometrial dating. The expressional profiles were clustered, and differential expression analysis was performed on the model development group, using 63 endometrial biopsies spanning over proliferative (PE, n = 18), early-secretory (ESE, n = 18), mid-secretory (MSE, n = 17) and late-secretory (LSE, n = 10) endometrial phases of the natural cycle. A quantitative predictor model was trained on the development group and validated on sequenced samples from healthy women, consisting of 52 paired samples taken from ESE and MSE phases and five LSE phase samples from 31 individuals. Finally, the developed test was applied to 44 MSE phase samples from a study group of patients diagnosed with recurrent implantation failure (RIF). In validation samples (n = 57), we detected displaced WOI in 1.8% of the samples from fertile women. In the RIF study group, we detected a significantly higher proportion of the samples with shifted WOI than in the validation set of samples from fertile women, 15.9% and 1.8% (p = 0.012), respectively. The developed model was evaluated with an average cross-validation accuracy of 98.8% and an accuracy of 98.2% in the validation group. The developed beREADY screening model enables sensitive and dynamic detection of selected transcriptome biomarkers, providing a quantitative and accurate prediction of endometrial receptivity status.

Fetal HLA-G mediated immune tolerance and interferon response in preeclampsia.

BACKGROUND: Fetal immune tolerance is crucial for pregnancy success. We studied the link between preeclampsia, a severe pregnancy disorder with uncertain pathogenesis, and fetal human leukocyte antigen G (HLA-G) and other genes regulating maternal immune responses. METHODS: We assessed sex ratios and regulatory HLA-G haplotypes in population cohorts and series of preeclampsia and stillbirth. We studied placental mRNA expression of 136 genes by sequencing and HLA-G and interferon alpha (IFNα) protein expression by immunohistochemistry. FINDINGS: We found underrepresentation of males in preeclamptic births, especially those delivered preterm or small for gestational age. Balancing selection at HLA-G associated with the sex ratio, stillbirth, and preeclampsia. We observed downregulation of HLA-G, its receptors, and many other tolerogenic genes, and marked upregulation of IFNA1 in preeclamptic placentas. INTERPRETATION: These findings indicate that an evolutionary trade-off between immune tolerance and protection against infections at the maternal-fetal interface promotes genetic diversity in fetal HLA-G, thereby affecting survival, preeclampsia, and sex ratio. We highlight IFNA1 as a potential mediator of preeclampsia and a target for therapeutic trials. FUNDING: Finnish Medical Foundation, Päivikki and Sakari Sohlberg Foundation, Karolinska Institutet Research Foundation, Scandinavia-Japan Sasakawa Foundation, Japan Eye Bank Association, Astellas Foundation for Research on Metabolic Disorders, Japan Society for the Promotion of Science, Knut and Alice Wallenberg Foundation, Swedish Research Council, Medical Society Liv och Hälsa, Sigrid Jusélius Foundation, Helsinki University Hospital and University of Helsinki, Jane and Aatos Erkko Foundation, Academy of Finland, Finska Läkaresällskapet, Novo Nordisk Foundation, Finnish Foundation for Pediatric Research, and Emil Aaltonen Foundation.

Computational framework for targeted high-coverage sequencing based NIPT.

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/m2). 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.

TAC-seq: targeted DNA and RNA sequencing for precise biomarker molecule counting.

Targeted next-generation sequencing (NGS) methods have become essential in medical research and diagnostics. In addition to NGS sensitivity and high-throughput capacity, precise biomolecule counting based on unique molecular identifier (UMI) has potential to increase biomolecule detection accuracy. Although UMIs are widely used in basic research its introduction to clinical assays is still in progress. Here, we present a robust and cost-effective TAC-seq (Targeted Allele Counting by sequencing) method that uses UMIs to estimate the original molecule counts of mRNAs, microRNAs, and cell-free DNA. We applied TAC-seq in three different clinical applications and compared the results with standard NGS. RNA samples extracted from human endometrial biopsies were analyzed using previously described 57 mRNA-based receptivity biomarkers and 49 selected microRNAs at different expression levels. Cell-free DNA aneuploidy testing was based on cell line (47,XX, +21) genomic DNA. TAC-seq mRNA profiling showed identical clustering results to transcriptome RNA sequencing, and microRNA detection demonstrated significant reduction in amplification bias, allowing to determine minor expression changes between different samples that remained undetermined by standard NGS. The mimicking experiment for cell-free DNA fetal aneuploidy analysis showed that TAC-seq can be applied to count highly fragmented DNA, detecting significant (p = 7.6 × 10-4) excess of chromosome 21 molecules at 10% fetal fraction level. Based on three proof-of-principle applications we demonstrate that TAC-seq is an accurate and highly potential biomarker profiling method for advanced medical research and diagnostics.

NIPTmer: rapid k-mer-based software package for detection of fetal aneuploidies.

Non-invasive prenatal testing (NIPT) is a recent and rapidly evolving method for detecting genetic lesions, such as aneuploidies, of a fetus. However, there is a need for faster and cheaper laboratory and analysis methods to make NIPT more widely accessible. We have developed a novel software package for detection of fetal aneuploidies from next-generation low-coverage whole genome sequencing data. Our tool - NIPTmer - is based on counting pre-defined per-chromosome sets of unique k-mers from raw sequencing data, and applying linear regression model on the counts. Additionally, the filtering process used for k-mer list creation allows one to take into account the genetic variance in a specific sample, thus reducing the source of uncertainty. The processing time of one sample is less than 10 CPU-minutes on a high-end workstation. NIPTmer was validated on a cohort of 583 NIPT samples and it correctly predicted 37 non-mosaic fetal aneuploidies. NIPTmer has the potential to reduce significantly the time and complexity of NIPT post-sequencing analysis compared to mapping-based methods. For non-commercial users the software package is freely available at http://bioinfo.ut.ee/NIPTMer/ .