Suunatud ja ülegenoomsel sekveneerimisel põhinevate mitteinvasiivsete sünnieelsete testide arvutusmeetodite ja töövoogude väljatöötamine

Väitekirja elektrooniline versioon ei sisalda publikatsiooneLoote sõeluuring võimaldab avastada lootel esinevaid arenguhäireid ja sagedasemaid kromosoomhaiguseid, nagu näiteks Down’i, Edwards’i ja Patau sündroom. Varajane teave lootel esineva kromosoomhaiguse kohta võimaldab langetada informeeritud otsust raseduse jätkamise osas ning aitab tulevasi vanemaid paremini ette valmistada. Tavapärane loote sõeluuring sisaldab loote ultraheli uuringut ja vereseerumi analüüsi, mille abil tuvastatakse enamik kromosoomhaigusega loodetest. Lõpliku diagnoosi saamiseks suunatakse kõrge riski saanud patsient edasi invasiivsele protseduurile. Eelnimetatud sõeluuringute puuduseks on arvestatav valepositiivsete hulk, mistõttu enamik positiivse testitulemuse saanud patsientidest kannab täiesti tervet loodet. Sõeluuringule järgnev invasiivne protseduur on neil juhtudel ebavajalik, põhjustab rasedatele asjatut stressi ning sellega võib kaasneda suurenenud oht raseduse katkemiseks. Antud doktoritöö keskseks teemaks on mitte-invasiivne sünnieelne testimine (NIPT), mis põhineb ema veres leiduva loote päritolu rakuvaba DNA analüüsil. Võrreldes eelmainitud traditsionaalsete sõeluuringu meetoditega, on NIPT oluliselt sensitiivsem ja spetsiifilisem sagedamini esinevate kromosoomihäirete avastamiseks. Doktoritöö raames arendati välja TAC-seq põhine analüüsi töövoog, mida rakendati 21. kromosoom trisoomia tuvastamiseks. Lisaks töötati välja NIPT analüüsiraamistik, mis kasutab erinevaid masinõppe metoodikaid loote trisoomia määramiseks rakuvaba DNA-st. Niisamuti viidi Eesti rasedate kohordil läbi NIPT metoodika validatsiooni uuring, milles rakendati ülegenoomsel sekveneerimisel põhinevat töövoogu sagedamate loote kromosoomihäirete määramiseks. Üldiselt on nii suunatud kui ka ülegenoomsel NIPT meetoditel muutnud rasedate sõeluuring varasemast veel täpsemaks. Kui suunatud sekveneerimise suureks eeliseks on kulutõhusus, siis ülegenoomne lähenemine tuvastab valimatult kõikvõimalikke geneetilisi aberratsioone üle kogu genoomi.Fetal screening allows to detect congenital anomalies and more frequent chromosomal abnormalities, such as Down, Edwards and Patau syndrome. Early information about a fetus’s possible health problem allows to make an informed decision about the continuation of the pregnancy and better prepare the future parents. Conventional screening includes an ultrasound and blood serum analysis by way of which most of the fetal chromosomal abnormalities are detected. For a final diagnosis, the patients who are deemed to have a high risk for fetal chromosomal aberrations are referred to an invasive procedure. The disadvantage of the aforementioned screening method is a considerable number of false positive results, which is why most of the patients who receive a positive result are actually carrying a fully healthy fetus. The invasive procedure that follows the screening is unnecessary for those patients, causes them undue stress and this may also lead to a higher risk of miscarriage. The focal point of this doctoral thesis is non-invasive prenatal testing (NIPT), which is based on the analysis of cell-free DNA (cfDNA) of fetal origin that is found in maternal blood. In comparison to the above-mentioned conventional screening methods, NIPT is considerably more sensitive and specific for detecting the most common chromosomal abnormalities. In the framework of the thesis, TAC-seq based analysis workflow was developed and used to detect chromosome 21 trisomy. In addition, NIPT analysis framework, which uses different machine learning methods, was developed for determining fetal trisomies from cfDNA sample. Also, a validation study of NIPT was carried out on pregnant women in Estonian cohort using a whole-genome sequencing based workflow. In general, both targeted and whole-genome sequencing based NIPT methods have made prenatal screening of fetal aneuplodies even more accurate than before. While cost-effectiveness is a major advantage of the targeted sequencing based approach, the whole-genome sequencing based NIPT possibly detects all kinds of genetic aberrations across the genome.https://www.ester.ee/record=b549777

Evaluation of the possibility to detect fetal chromosome trisomies based on a defined set of single nucleotide polymorphisms for non-invasive prenatal testing

Non-invasive prenatal testing (NIPT) of fetal aneuploidy using cell-free fetal (cffDNA) from mother’s blood sample has shown to be an accurate and reliable screening tool. The current NIPT protocols are based on targeted or whole genome sequencing, which demand resource-intensive bioinformatical capacity. The complexity of current NIPT technology is trustworthy but the comprehensive adaption of the application is still limited due to the high cost. Mother- and fetus-specific genotypes, according to the nature of cell-free DNA (cfDNA) during pregnancy, were simulated and used in further analysis. Simulations and theoretical calculations demonstrate the characteristic patterns of allelic ratios in case of normal number of chromosomes or trisomy where extra chromosome is inherited from mother or father. Here described analytical approach managed to identify fetal trisomy by comparing the allelic ratios of the risk chromosome with the expected allelic ratios using the t-test and hidden Markov model (HMM) analysis. An average, 3/4 of all highly polymorphic single nucleotide polymorphisms (SNPs) can be used in analysis based on comparison of the allelic ratios. As a result, at least 300 highly polymorphic SNPs over risk and reference chromosomes are needed to detect fetal trisomy using t-test alone. In addition, the HMM analysis can independently detect fetal trisomy and have the ability to distinguish the parental origin of trisomy. Based on the simulated data, the existence and the origin of fetal trisomy is theoretically detectable using a novel and highly quantitative SNP-based approach that is under development by our research group. However, further testing has to be carried out with the real data to confirm the theory

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

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

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 (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.Peer reviewe

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.Peer reviewe

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/.Peer reviewe

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

A molecular tool for menstrual cycle phase dating of endometrial samples in endometriosis transcriptome studies

Correction: Volume: 101 Issue: 4 Pages: 868-868 DOI: 10.1093/biolre/ioz092Non peer reviewe