Spolupracovali sme na publikáciach
2024
11.
Holesova, Z.; Pös, O.; Gazdarica, J.; Kucharik, M.; Budis, J.; Hyblova, M.; Minarik, G.; Szemes, T.
Understanding genetic variability: exploring large-scale copy number variants through non-invasive prenatal testing in European populations Journal Article
V: BMC Genomics, 25 (1), 2024, ISSN: 14712164.
Abstrakt | Linky | BibTeX | Značky: Copy number variation, Non-invasive prenatal testing, Population study
@article{Holesova2024,
title = {Understanding genetic variability: exploring large-scale copy number variants through non-invasive prenatal testing in European populations},
author = {Z. Holesova and O. Pös and J. Gazdarica and M. Kucharik and J. Budis and M. Hyblova and G. Minarik and T. Szemes},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190362328&doi=10.1186%2fs12864-024-10267-5&partnerID=40&md5=9db9ad228e071b255f5c759790d53c82},
doi = {10.1186/s12864-024-10267-5},
issn = {14712164},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {BMC Genomics},
volume = {25},
number = {1},
publisher = {BioMed Central Ltd},
abstract = {Large-scale copy number variants (CNVs) are structural alterations in the genome that involve the duplication or deletion of DNA segments, contributing to genetic diversity and playing a crucial role in the evolution and development of various diseases and disorders, as they can lead to the dosage imbalance of one or more genes. Massively parallel sequencing (MPS) has revolutionized the field of genetic analysis and contributed significantly to routine clinical diagnosis and screening. It offers a precise method for detecting CNVs with exceptional accuracy. In this context, a non-invasive prenatal test (NIPT) based on the sequencing of cell-free DNA (cfDNA) from pregnant women’s plasma using a low-coverage whole genome MPS (WGS) approach represents a valuable source for population studies. Here, we analyzed genomic data of 12,732 pregnant women from the Slovak (9,230), Czech (1,583), and Hungarian (1,919) populations. We identified 5,062 CNVs ranging from 200 kbp and described their basic characteristics and differences between the subject populations. Our results suggest that re-analysis of sequencing data from routine WGS assays has the potential to obtain large-scale CNV population frequencies, which are not well known and may provide valuable information to support the classification and interpretation of this type of genetic variation. Furthermore, this could contribute to expanding knowledge about the central European genome without investing in additional laboratory work, as NIPTs are a relatively widely used screening method. © The Author(s) 2024.},
keywords = {Copy number variation, Non-invasive prenatal testing, Population study},
pubstate = {published},
tppubtype = {article}
}
Large-scale copy number variants (CNVs) are structural alterations in the genome that involve the duplication or deletion of DNA segments, contributing to genetic diversity and playing a crucial role in the evolution and development of various diseases and disorders, as they can lead to the dosage imbalance of one or more genes. Massively parallel sequencing (MPS) has revolutionized the field of genetic analysis and contributed significantly to routine clinical diagnosis and screening. It offers a precise method for detecting CNVs with exceptional accuracy. In this context, a non-invasive prenatal test (NIPT) based on the sequencing of cell-free DNA (cfDNA) from pregnant women’s plasma using a low-coverage whole genome MPS (WGS) approach represents a valuable source for population studies. Here, we analyzed genomic data of 12,732 pregnant women from the Slovak (9,230), Czech (1,583), and Hungarian (1,919) populations. We identified 5,062 CNVs ranging from 200 kbp and described their basic characteristics and differences between the subject populations. Our results suggest that re-analysis of sequencing data from routine WGS assays has the potential to obtain large-scale CNV population frequencies, which are not well known and may provide valuable information to support the classification and interpretation of this type of genetic variation. Furthermore, this could contribute to expanding knowledge about the central European genome without investing in additional laboratory work, as NIPTs are a relatively widely used screening method. © The Author(s) 2024.
10.
Lukáčová, E.; Pös, O.; Túryová, E.; Hurtová, T.; Hanzlíková, Z.; Szemes, T.; Burjanivová, T.
Copy number variations in malignant melanoma: genomic regions, biomarkers, and therapeutic targets Journal Article
V: Neoplasma, 71 (2), pp. 143-152, 2024, ISSN: 00282685.
Abstrakt | Linky | BibTeX | Značky: Copy number variation, Oncology
@article{Lukáčová2024143,
title = {Copy number variations in malignant melanoma: genomic regions, biomarkers, and therapeutic targets},
author = {E. Lukáčová and O. Pös and E. Túryová and T. Hurtová and Z. Hanzlíková and T. Szemes and T. Burjanivová},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193674159&doi=10.4149%2fneo_2024_240207N58&partnerID=40&md5=eda6c5ac3bdd1a7f4c629f9b73bbaa44},
doi = {10.4149/neo_2024_240207N58},
issn = {00282685},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {Neoplasma},
volume = {71},
number = {2},
pages = {143-152},
abstract = {Malignant melanoma is a skin tumor arising from melanocytes, occurring mostly in predisposed individuals. Melanomas are frequently present with copy number variations (CNVs), i.e., gains or losses of specific DNA regions that have provided immense potential for disease diagnosis and classification. The methodology of CNV detection has revolutionized in past decades, and current high throughput technologies enable us to analyze the entire spectrum of CNV alterations at the whole genome scale. Thus, identifying novel CNV biomarkers and evaluating their applicability in biomedicine are becoming increasingly important. The aim of this review was to summarize copy number changes occurring in malignant melanomas. We made an overview of specific genes and chromosomal locations affected in sporadic and familial melanoma and also of known germline alterations in melanoma-prone families. We summarized genomic regions aberrant in malignant melanoma and highlighted those frequently discussed in the literature, suggesting 7q, 11q, 12q, 9p, and 1q, but also others, as the most affected ones.},
keywords = {Copy number variation, Oncology},
pubstate = {published},
tppubtype = {article}
}
Malignant melanoma is a skin tumor arising from melanocytes, occurring mostly in predisposed individuals. Melanomas are frequently present with copy number variations (CNVs), i.e., gains or losses of specific DNA regions that have provided immense potential for disease diagnosis and classification. The methodology of CNV detection has revolutionized in past decades, and current high throughput technologies enable us to analyze the entire spectrum of CNV alterations at the whole genome scale. Thus, identifying novel CNV biomarkers and evaluating their applicability in biomedicine are becoming increasingly important. The aim of this review was to summarize copy number changes occurring in malignant melanomas. We made an overview of specific genes and chromosomal locations affected in sporadic and familial melanoma and also of known germline alterations in melanoma-prone families. We summarized genomic regions aberrant in malignant melanoma and highlighted those frequently discussed in the literature, suggesting 7q, 11q, 12q, 9p, and 1q, but also others, as the most affected ones.
2023
9.
Sládeček, T.; Gažiová, M.; Kucharík, M.; Zaťková, A.; Pös, Z.; Pös, O.; Krampl, W.; Tomková, E.; Hýblová, M.; Minárik, G.; Radvánszky, J.; Budiš, J.; Szemes, T.
V: Scientific Reports, 13 (1), 2023, ISSN: 20452322.
Abstrakt | Linky | BibTeX | Značky: Computational method, Copy number variation
@article{Sládeček2023,
title = {Combination of expert guidelines-based and machine learning-based approaches leads to superior accuracy of automated prediction of clinical effect of copy number variations},
author = {T. Sládeček and M. Gažiová and M. Kucharík and A. Zaťková and Z. Pös and O. Pös and W. Krampl and E. Tomková and M. Hýblová and G. Minárik and J. Radvánszky and J. Budiš and T. Szemes},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163886010&doi=10.1038%2fs41598-023-37352-1&partnerID=40&md5=9752e9d83f2d1eca8a028bdffc3fd1f8},
doi = {10.1038/s41598-023-37352-1},
issn = {20452322},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
journal = {Scientific Reports},
volume = {13},
number = {1},
publisher = {Nature Research},
abstract = {Clinical interpretation of copy number variants (CNVs) is a complex process that requires skilled clinical professionals. General recommendations have been recently released to guide the CNV interpretation based on predefined criteria to uniform the decision process. Several semiautomatic computational methods have been proposed to recommend appropriate choices, relieving clinicians of tedious searching in vast genomic databases. We have developed and evaluated such a tool called MarCNV and tested it on CNV records collected from the ClinVar database. Alternatively, the emerging machine learning-based tools, such as the recently published ISV (Interpretation of Structural Variants), showed promising ways of even fully automated predictions using broader characterization of affected genomic elements. Such tools utilize features additional to ACMG criteria, thus providing supporting evidence and the potential to improve CNV classification. Since both approaches contribute to evaluation of CNVs clinical impact, we propose a combined solution in the form of a decision support tool based on automated ACMG guidelines (MarCNV) supplemented by a machine learning-based pathogenicity prediction (ISV) for the classification of CNVs. We provide evidence that such a combined approach is able to reduce the number of uncertain classifications and reveal potentially incorrect classifications using automated guidelines. CNV interpretation using MarCNV, ISV, and combined approach is available for non-commercial use at https://predict.genovisio.com/ . © 2023, The Author(s).},
keywords = {Computational method, Copy number variation},
pubstate = {published},
tppubtype = {article}
}
Clinical interpretation of copy number variants (CNVs) is a complex process that requires skilled clinical professionals. General recommendations have been recently released to guide the CNV interpretation based on predefined criteria to uniform the decision process. Several semiautomatic computational methods have been proposed to recommend appropriate choices, relieving clinicians of tedious searching in vast genomic databases. We have developed and evaluated such a tool called MarCNV and tested it on CNV records collected from the ClinVar database. Alternatively, the emerging machine learning-based tools, such as the recently published ISV (Interpretation of Structural Variants), showed promising ways of even fully automated predictions using broader characterization of affected genomic elements. Such tools utilize features additional to ACMG criteria, thus providing supporting evidence and the potential to improve CNV classification. Since both approaches contribute to evaluation of CNVs clinical impact, we propose a combined solution in the form of a decision support tool based on automated ACMG guidelines (MarCNV) supplemented by a machine learning-based pathogenicity prediction (ISV) for the classification of CNVs. We provide evidence that such a combined approach is able to reduce the number of uncertain classifications and reveal potentially incorrect classifications using automated guidelines. CNV interpretation using MarCNV, ISV, and combined approach is available for non-commercial use at https://predict.genovisio.com/ . © 2023, The Author(s).
2022
8.
Gažiová, M.; Sládeček, T.; Pös, O.; Števko, M.; Krampl, W.; Pös, Z.; Hekel, R.; Hlavačka, M.; Kucharík, M.; Radvánszky, J.; Budiš, J.; Szemes, T.
Automated prediction of the clinical impact of structural copy number variations Journal Article
V: Scientific Reports, 12 (1), 2022, ISSN: 20452322.
Abstrakt | Linky | BibTeX | Značky: Computational method, Copy number variation, Variant interpretation
@article{Gažiová2022,
title = {Automated prediction of the clinical impact of structural copy number variations},
author = {M. Gažiová and T. Sládeček and O. Pös and M. Števko and W. Krampl and Z. Pös and R. Hekel and M. Hlavačka and M. Kucharík and J. Radvánszky and J. Budiš and T. Szemes},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122796228&doi=10.1038%2fs41598-021-04505-z&partnerID=40&md5=2826a9187c8d22af2fdc6f5d22911cf2},
doi = {10.1038/s41598-021-04505-z},
issn = {20452322},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {Scientific Reports},
volume = {12},
number = {1},
publisher = {Nature Research},
abstract = {Copy number variants (CNVs) play an important role in many biological processes, including the development of genetic diseases, making them attractive targets for genetic analyses. The interpretation of the effect of these structural variants is a challenging problem due to highly variable numbers of gene, regulatory, or other genomic elements affected by the CNV. This led to the demand for the interpretation tools that would relieve researchers, laboratory diagnosticians, genetic counselors, and clinical geneticists from the laborious process of annotation and classification of CNVs. We designed and validated a prediction method (ISV; Interpretation of Structural Variants) that is based on boosted trees which takes into account annotations of CNVs from several publicly available databases. The presented approach achieved more than 98% prediction accuracy on both copy number loss and copy number gain variants while also allowing CNVs being assigned “uncertain” significance in predictions. We believe that ISV’s prediction capability and explainability have a great potential to guide users to more precise interpretations and classifications of CNVs. © 2022, The Author(s).},
keywords = {Computational method, Copy number variation, Variant interpretation},
pubstate = {published},
tppubtype = {article}
}
Copy number variants (CNVs) play an important role in many biological processes, including the development of genetic diseases, making them attractive targets for genetic analyses. The interpretation of the effect of these structural variants is a challenging problem due to highly variable numbers of gene, regulatory, or other genomic elements affected by the CNV. This led to the demand for the interpretation tools that would relieve researchers, laboratory diagnosticians, genetic counselors, and clinical geneticists from the laborious process of annotation and classification of CNVs. We designed and validated a prediction method (ISV; Interpretation of Structural Variants) that is based on boosted trees which takes into account annotations of CNVs from several publicly available databases. The presented approach achieved more than 98% prediction accuracy on both copy number loss and copy number gain variants while also allowing CNVs being assigned “uncertain” significance in predictions. We believe that ISV’s prediction capability and explainability have a great potential to guide users to more precise interpretations and classifications of CNVs. © 2022, The Author(s).
7.
Soltész, B.; Pös, O.; Wlachovska, Z.; Budis, J.; Hekel, R.; Strieskova, L.; Liptak, J. B.; Krampl, W.; Styk, J.; Németh, N.; Keserű, J. S.; Jenei, A.; Buglyó, G.; Klekner, Á.; Nagy, B.; Szemes, T.
Mitochondrial DNA copy number changes, heteroplasmy, and mutations in plasma-derived exosomes and brain tissue of glioblastoma patients Journal Article
V: Molecular and Cellular Probes, 66 , 2022, ISSN: 08908508.
Abstrakt | Linky | BibTeX | Značky: Copy number variation, Mitochondria, Oncology
@article{Soltész2022b,
title = {Mitochondrial DNA copy number changes, heteroplasmy, and mutations in plasma-derived exosomes and brain tissue of glioblastoma patients},
author = {B. Soltész and O. Pös and Z. Wlachovska and J. Budis and R. Hekel and L. Strieskova and J. B. Liptak and W. Krampl and J. Styk and N. Németh and J. S. Keserű and A. Jenei and G. Buglyó and Á. Klekner and B. Nagy and T. Szemes},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142723801&doi=10.1016%2fj.mcp.2022.101875&partnerID=40&md5=cfe8239029a20ab89e08e1321a98c75e},
doi = {10.1016/j.mcp.2022.101875},
issn = {08908508},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {Molecular and Cellular Probes},
volume = {66},
publisher = {Academic Press},
abstract = {Glioblastoma is the most common malignant tumor of the central nervous system (CNS) in adults. Glioblastoma cells show increased glucose consumption associated with poor prognosis. Since mitochondria play a crucial role in energy metabolism, mutations and copy number changes of mitochondrial DNA may serve as biomarkers. As the brain is difficult to access, analysis of mitochondria directly from the brain tissue represents a challenge. Exosome analysis is an alternative (still poorly explored) approach to investigate molecular changes in CNS tumors. We analyzed brain tissue DNA and plasma-derived exosomal DNA (exoDNA) of 44 glioblastoma patients and 40 control individuals. Quantitative real-time PCR was performed to determine mtDNA copy numbers and the Kruskal-Wallis and Mann-Whitney U test were used for statistical analysis of data. Subsequently, sequencing libraries were prepared and sequenced on the MiSeq platform to identify mtDNA point mutations. Tissue mtDNA copy number was different among controls and patients in multiple comparisons. A similar tendency was detected in exosomes. Based on NGS analysis, several mtDNA point mutations showed slightly different frequencies between cases and controls, but the clinical relevance of these observations is difficult to assess and likely less than that of overall mtDNA copy number changes. Allele frequencies of variants were used to determine the level of heteroplasmy (found to be higher in exo-mtDNA of control individuals). Despite the suggested potential, the use of such biomarkers for the screening and/or diagnosis of glioblastomas is still limited, thus further studies are needed. © 2022},
keywords = {Copy number variation, Mitochondria, Oncology},
pubstate = {published},
tppubtype = {article}
}
Glioblastoma is the most common malignant tumor of the central nervous system (CNS) in adults. Glioblastoma cells show increased glucose consumption associated with poor prognosis. Since mitochondria play a crucial role in energy metabolism, mutations and copy number changes of mitochondrial DNA may serve as biomarkers. As the brain is difficult to access, analysis of mitochondria directly from the brain tissue represents a challenge. Exosome analysis is an alternative (still poorly explored) approach to investigate molecular changes in CNS tumors. We analyzed brain tissue DNA and plasma-derived exosomal DNA (exoDNA) of 44 glioblastoma patients and 40 control individuals. Quantitative real-time PCR was performed to determine mtDNA copy numbers and the Kruskal-Wallis and Mann-Whitney U test were used for statistical analysis of data. Subsequently, sequencing libraries were prepared and sequenced on the MiSeq platform to identify mtDNA point mutations. Tissue mtDNA copy number was different among controls and patients in multiple comparisons. A similar tendency was detected in exosomes. Based on NGS analysis, several mtDNA point mutations showed slightly different frequencies between cases and controls, but the clinical relevance of these observations is difficult to assess and likely less than that of overall mtDNA copy number changes. Allele frequencies of variants were used to determine the level of heteroplasmy (found to be higher in exo-mtDNA of control individuals). Despite the suggested potential, the use of such biomarkers for the screening and/or diagnosis of glioblastomas is still limited, thus further studies are needed. © 2022
6.
Hyblova, M.; Gnip, A.; Kucharik, M.; Budis, J.; Sekelska, M.; Minarik, G.
Maternal Copy Number Imbalances in Non-Invasive Prenatal Testing: Do They Matter? Journal Article
V: Diagnostics, 12 (12), 2022, ISSN: 20754418.
Abstrakt | Linky | BibTeX | Značky: Copy number variation, Non-invasive prenatal testing
@article{Hyblova2022,
title = {Maternal Copy Number Imbalances in Non-Invasive Prenatal Testing: Do They Matter?},
author = {M. Hyblova and A. Gnip and M. Kucharik and J. Budis and M. Sekelska and G. Minarik},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144618980&doi=10.3390%2fdiagnostics12123056&partnerID=40&md5=3f313608e34c3a2137159e1e157d014c},
doi = {10.3390/diagnostics12123056},
issn = {20754418},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {Diagnostics},
volume = {12},
number = {12},
publisher = {MDPI},
abstract = {Non-invasive prenatal testing (NIPT) has become a routine practice in screening for common aneuploidies of chromosomes 21, 18, and 13 and gonosomes X and Y in fetuses worldwide since 2015 and has even expanded to include smaller subchromosomal events. In fact, the fetal fraction represents only a small proportion of cell-free DNA on a predominant background of maternal DNA. Unlike fetal findings that have to be confirmed using invasive testing, it has been well documented that NIPT provides information on maternal mosaicism, occult malignancies, and hidden health conditions due to copy number variations (CNVs) with diagnostic resolution. Although large duplications or deletions associated with certain medical conditions or syndromes are usually well recognized and easy to interpret, very little is known about small, relatively common copy number variations on the order of a few hundred kilobases and their potential impact on human health. We analyzed data from 6422 NIPT patient samples with a CNV detection resolution of 200 kb for the maternal genome and identified 942 distinct CNVs; 328 occurred repeatedly. We defined them as multiple occurring variants (MOVs). We scrutinized the most common ones, compared them with frequencies in the gnomAD SVs v2.1, dbVar, and DGV population databases, and analyzed them with an emphasis on genomic content and potential association with specific phenotypes. © 2022 by the authors.},
keywords = {Copy number variation, Non-invasive prenatal testing},
pubstate = {published},
tppubtype = {article}
}
Non-invasive prenatal testing (NIPT) has become a routine practice in screening for common aneuploidies of chromosomes 21, 18, and 13 and gonosomes X and Y in fetuses worldwide since 2015 and has even expanded to include smaller subchromosomal events. In fact, the fetal fraction represents only a small proportion of cell-free DNA on a predominant background of maternal DNA. Unlike fetal findings that have to be confirmed using invasive testing, it has been well documented that NIPT provides information on maternal mosaicism, occult malignancies, and hidden health conditions due to copy number variations (CNVs) with diagnostic resolution. Although large duplications or deletions associated with certain medical conditions or syndromes are usually well recognized and easy to interpret, very little is known about small, relatively common copy number variations on the order of a few hundred kilobases and their potential impact on human health. We analyzed data from 6422 NIPT patient samples with a CNV detection resolution of 200 kb for the maternal genome and identified 942 distinct CNVs; 328 occurred repeatedly. We defined them as multiple occurring variants (MOVs). We scrutinized the most common ones, compared them with frequencies in the gnomAD SVs v2.1, dbVar, and DGV population databases, and analyzed them with an emphasis on genomic content and potential association with specific phenotypes. © 2022 by the authors.
2021
5.
Pös, O; Radvanszky, J; Styk, J; Pös, Z; Buglyó, G; Kajsik, M; Budis, J; Nagy, B; Szemes, T
Copy number variation: Methods and clinical applications Journal Article
V: Applied Sciences (Switzerland), 11 (2), pp. 1-16, 2021, ISSN: 20763417.
Abstrakt | Linky | BibTeX | Značky: Copy number variation, Review, Variant interpretation
@article{Pös20211,
title = {Copy number variation: Methods and clinical applications},
author = {O Pös and J Radvanszky and J Styk and Z Pös and G Buglyó and M Kajsik and J Budis and B Nagy and T Szemes},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099826325&doi=10.3390%2fapp11020819&partnerID=40&md5=bf6fb8a1dd856194a109626d3ad1f9ca},
doi = {10.3390/app11020819},
issn = {20763417},
year = {2021},
date = {2021-01-01},
journal = {Applied Sciences (Switzerland)},
volume = {11},
number = {2},
pages = {1-16},
publisher = {MDPI AG},
abstract = {Gains and losses of large segments of genomic DNA, known as copy number variants (CNVs) gained considerable interest in clinical diagnostics lately, as particular forms may lead to inherited genetic diseases. In recent decades, researchers developed a wide variety of cytogenetic and molecular methods with different detection capabilities to detect clinically relevant CNVs. In this review, we summarize methodological progress from conventional approaches to current state of the art techniques capable of detecting CNVs from a few bases up to several megabases. Although the recent rapid progress of sequencing methods has enabled precise detection of CNVs, determining their functional effect on cellular and whole-body physiology remains a challenge. Here, we provide a comprehensive list of databases and bioinformatics tools that may serve as useful assets for researchers, laboratory diagnosticians, and clinical geneticists facing the challenge of CNV detection and interpretation. © 2021 by the authors.},
keywords = {Copy number variation, Review, Variant interpretation},
pubstate = {published},
tppubtype = {article}
}
Gains and losses of large segments of genomic DNA, known as copy number variants (CNVs) gained considerable interest in clinical diagnostics lately, as particular forms may lead to inherited genetic diseases. In recent decades, researchers developed a wide variety of cytogenetic and molecular methods with different detection capabilities to detect clinically relevant CNVs. In this review, we summarize methodological progress from conventional approaches to current state of the art techniques capable of detecting CNVs from a few bases up to several megabases. Although the recent rapid progress of sequencing methods has enabled precise detection of CNVs, determining their functional effect on cellular and whole-body physiology remains a challenge. Here, we provide a comprehensive list of databases and bioinformatics tools that may serve as useful assets for researchers, laboratory diagnosticians, and clinical geneticists facing the challenge of CNV detection and interpretation. © 2021 by the authors.
4.
Kucharík, M; Budiš, J; Hýblová, M; Minárik, G; Szemes, T
Copy number variant detection with low-coverage whole-genome sequencing represents a viable alternative to the conventional array-cgh Journal Article
V: Diagnostics, 11 (4), 2021, ISSN: 20754418.
Abstrakt | Linky | BibTeX | Značky: Cell-free nucleic acids, Computational method, Copy number variation, Liquid biopsy, Non-invasive prenatal testing
@article{Kucharík2021,
title = {Copy number variant detection with low-coverage whole-genome sequencing represents a viable alternative to the conventional array-cgh},
author = {M Kucharík and J Budiš and M Hýblová and G Minárik and T Szemes},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109087040&doi=10.3390%2fdiagnostics11040708&partnerID=40&md5=6fdfa35027032bf889399d967bb1cce9},
doi = {10.3390/diagnostics11040708},
issn = {20754418},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Diagnostics},
volume = {11},
number = {4},
publisher = {MDPI AG},
abstract = {Copy number variations (CNVs) represent a type of structural variant involving alterations in the number of copies of specific regions of DNA that can either be deleted or duplicated. CNVs contribute substantially to normal population variability, however, abnormal CNVs cause numerous genetic disorders. At present, several methods for CNV detection are applied, ranging from the conventional cytogenetic analysis, through microarray-based methods (aCGH), to next-generation sequencing (NGS). In this paper, we present GenomeScreen, an NGS-based CNV detection method for low-coverage, whole-genome sequencing. We determined the theoretical limits of its accuracy and obtained confirmation in an extensive in silico study and in real patient samples with known genotypes. In theory, at least 6 M uniquely mapped reads are required to detect a CNV with the length of 100 kilobases (kb) or more with high confidence (Z-score > 7). In practice, the in silico analysis required at least 8 M to obtain >99% accuracy (for 100 kb deviations). We compared GenomeScreen with one of the currently used aCGH methods in diagnostic laboratories, which has mean resolution of 200 kb. GenomeScreen and aCGH both detected 59 deviations, while GenomeScreen furthermore detected 134 other (usually) smaller variations. When compared to aCGH, overall performance of the proposed GenemoScreen tool is comparable or superior in terms of accuracy, turn-around time, and cost-effectiveness, thus providing reasonable benefits, particularly in a prenatal diagnosis setting. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.},
keywords = {Cell-free nucleic acids, Computational method, Copy number variation, Liquid biopsy, Non-invasive prenatal testing},
pubstate = {published},
tppubtype = {article}
}
Copy number variations (CNVs) represent a type of structural variant involving alterations in the number of copies of specific regions of DNA that can either be deleted or duplicated. CNVs contribute substantially to normal population variability, however, abnormal CNVs cause numerous genetic disorders. At present, several methods for CNV detection are applied, ranging from the conventional cytogenetic analysis, through microarray-based methods (aCGH), to next-generation sequencing (NGS). In this paper, we present GenomeScreen, an NGS-based CNV detection method for low-coverage, whole-genome sequencing. We determined the theoretical limits of its accuracy and obtained confirmation in an extensive in silico study and in real patient samples with known genotypes. In theory, at least 6 M uniquely mapped reads are required to detect a CNV with the length of 100 kilobases (kb) or more with high confidence (Z-score > 7). In practice, the in silico analysis required at least 8 M to obtain >99% accuracy (for 100 kb deviations). We compared GenomeScreen with one of the currently used aCGH methods in diagnostic laboratories, which has mean resolution of 200 kb. GenomeScreen and aCGH both detected 59 deviations, while GenomeScreen furthermore detected 134 other (usually) smaller variations. When compared to aCGH, overall performance of the proposed GenemoScreen tool is comparable or superior in terms of accuracy, turn-around time, and cost-effectiveness, thus providing reasonable benefits, particularly in a prenatal diagnosis setting. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
2020
3.
Hyblova, M; Harsanyova, M; Nikulenkov-Grochova, D; Kadlecova, J; Kucharik, M; Budis, J; Minarik, G
V: Diagnostics, 10 (8), 2020, ISSN: 20754418.
Abstrakt | Linky | BibTeX | Značky: Copy number variation, Fetal fraction, Non-invasive prenatal testing, Validation
@article{Hyblova2020,
title = {Validation of copy number variants detection from pregnant plasma using low-pass whole-genome sequencing in noninvasive prenatal testing-like settings},
author = {M Hyblova and M Harsanyova and D Nikulenkov-Grochova and J Kadlecova and M Kucharik and J Budis and G Minarik},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090251668&doi=10.3390%2fdiagnostics10080569&partnerID=40&md5=b34f5ed83d4c332d97149be1644573c0},
doi = {10.3390/diagnostics10080569},
issn = {20754418},
year = {2020},
date = {2020-01-01},
journal = {Diagnostics},
volume = {10},
number = {8},
publisher = {MDPI AG},
abstract = {Detection of copy number variants as an integral part of noninvasive prenatal testing is increasingly used in clinical practice worldwide. We performed validation on plasma samples from 34 pregnant women with known aberrations using cell-free DNA sequencing to evaluate the sensitivity for copy number variants (CNV) detection using an in-house CNV fraction-based detection algorithm. The sensitivity for CNVs smaller than 3 megabases (Mb), larger than 3Mb, and overall was 78.57%, 100%, and 90.6%, respectively. Regarding the fetal fraction, detection sensitivity in the group with a fetal fraction of less than 10% was 57.14%, whereas there was 100% sensitivity in the group with fetal fraction exceeding 10%. The assay is also capable of indicating whether the origin of an aberration is exclusively fetal or fetomaternal/maternal. This validation demonstrated that a CNV fraction-based algorithm was applicable and feasible in clinical settings as a supplement to testing for common trisomies 21, 18, and 13. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).},
keywords = {Copy number variation, Fetal fraction, Non-invasive prenatal testing, Validation},
pubstate = {published},
tppubtype = {article}
}
Detection of copy number variants as an integral part of noninvasive prenatal testing is increasingly used in clinical practice worldwide. We performed validation on plasma samples from 34 pregnant women with known aberrations using cell-free DNA sequencing to evaluate the sensitivity for copy number variants (CNV) detection using an in-house CNV fraction-based detection algorithm. The sensitivity for CNVs smaller than 3 megabases (Mb), larger than 3Mb, and overall was 78.57%, 100%, and 90.6%, respectively. Regarding the fetal fraction, detection sensitivity in the group with a fetal fraction of less than 10% was 57.14%, whereas there was 100% sensitivity in the group with fetal fraction exceeding 10%. The assay is also capable of indicating whether the origin of an aberration is exclusively fetal or fetomaternal/maternal. This validation demonstrated that a CNV fraction-based algorithm was applicable and feasible in clinical settings as a supplement to testing for common trisomies 21, 18, and 13. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
2.
Kucharik, M; Gnip, A; Hyblova, M; Budis, J; Strieskova, L; Harsanyova, M; Pös, O; Kubiritova, Z; Radvanszky, J; Minarik, G; Szemes, T
Non-invasive prenatal testing (NIPT) by low coverage genomic sequencing: Detection limits of screened chromosomal microdeletions Journal Article
V: PLoS ONE, 15 (8 August), 2020, ISSN: 19326203.
Abstrakt | Linky | BibTeX | Značky: Copy number variation, Fetal fraction, Non-invasive prenatal testing, Validation
@article{Kucharik2020,
title = {Non-invasive prenatal testing (NIPT) by low coverage genomic sequencing: Detection limits of screened chromosomal microdeletions},
author = {M Kucharik and A Gnip and M Hyblova and J Budis and L Strieskova and M Harsanyova and O Pös and Z Kubiritova and J Radvanszky and G Minarik and T Szemes},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089990305&doi=10.1371%2fjournal.pone.0238245&partnerID=40&md5=56850bc0c9e9e5e266a3538da3dd5bed},
doi = {10.1371/journal.pone.0238245},
issn = {19326203},
year = {2020},
date = {2020-01-01},
journal = {PLoS ONE},
volume = {15},
number = {8 August},
publisher = {Public Library of Science},
abstract = {To study the detection limits of chromosomal microaberrations in non-invasive prenatal testing with aim for five target microdeletion syndromes, including DiGeorge, Prader-Willi/Angelman, 1p36, Cri-Du-Chat, and Wolf-Hirschhorn syndromes. We used known cases of pathogenic deletions from ISCA database to specifically define regions critical for the target syndromes. Our approach to detect microdeletions, from whole genome sequencing data, is based on sample normalization and read counting for individual bins. We performed both an in-silico study using artificially created data sets and a laboratory test on mixed DNA samples, with known microdeletions, to assess the sensitivity of prediction for varying fetal fractions, deletion lengths, and sequencing read counts. The in-silico study showed sensitivity of 79.3% for 10% fetal fraction with 20M read count, which further increased to 98.4% if we searched only for deletions longer than 3Mb. The test on laboratory-prepared mixed samples was in agreement with in-silico results, while we were able to correctly detect 24 out of 29 control samples. Our results suggest that it is possible to incorporate microaberration detection into basic NIPT as part of the offered screening/diagnostics procedure, however, accuracy and reliability depends on several specific factors. Copyright: © 2020 Kucharik et al.},
keywords = {Copy number variation, Fetal fraction, Non-invasive prenatal testing, Validation},
pubstate = {published},
tppubtype = {article}
}
To study the detection limits of chromosomal microaberrations in non-invasive prenatal testing with aim for five target microdeletion syndromes, including DiGeorge, Prader-Willi/Angelman, 1p36, Cri-Du-Chat, and Wolf-Hirschhorn syndromes. We used known cases of pathogenic deletions from ISCA database to specifically define regions critical for the target syndromes. Our approach to detect microdeletions, from whole genome sequencing data, is based on sample normalization and read counting for individual bins. We performed both an in-silico study using artificially created data sets and a laboratory test on mixed DNA samples, with known microdeletions, to assess the sensitivity of prediction for varying fetal fractions, deletion lengths, and sequencing read counts. The in-silico study showed sensitivity of 79.3% for 10% fetal fraction with 20M read count, which further increased to 98.4% if we searched only for deletions longer than 3Mb. The test on laboratory-prepared mixed samples was in agreement with in-silico results, while we were able to correctly detect 24 out of 29 control samples. Our results suggest that it is possible to incorporate microaberration detection into basic NIPT as part of the offered screening/diagnostics procedure, however, accuracy and reliability depends on several specific factors. Copyright: © 2020 Kucharik et al.
2019
1.
Pös, O; Budis, J; Kubiritova, Z; Kucharik, M; Duris, F; Radvanszky, J; Szemes, T
Identification of structural variation from NGS-based non-invasive prenatal testing Journal Article
V: International Journal of Molecular Sciences, 20 (18), 2019, ISSN: 16616596.
Abstrakt | Linky | BibTeX | Značky: Copy number variation, Non-invasive prenatal testing, Population study
@article{Pös2019,
title = {Identification of structural variation from NGS-based non-invasive prenatal testing},
author = {O Pös and J Budis and Z Kubiritova and M Kucharik and F Duris and J Radvanszky and T Szemes},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071973486&doi=10.3390%2fijms20184403&partnerID=40&md5=2b201ce501881c47092d14454e2ed2a9},
doi = {10.3390/ijms20184403},
issn = {16616596},
year = {2019},
date = {2019-01-01},
journal = {International Journal of Molecular Sciences},
volume = {20},
number = {18},
publisher = {MDPI AG},
abstract = {Copy number variants (CNVs) are an important type of human genome variation, which play a significant role in evolution contribute to population diversity and human genetic diseases. In recent years, next generation sequencing has become a valuable tool for clinical diagnostics and to provide sensitive and accurate approaches for detecting CNVs. In our previous work, we described a non-invasive prenatal test (NIPT) based on low-coverage massively parallel whole-genome sequencing of total plasma DNA for detection of CNV aberrations ≥600 kbp. We reanalyzed NIPT genomic data from 5018 patients to evaluate CNV aberrations in the Slovak population. Our analysis of autosomal chromosomes identified 225 maternal CNVs (47 deletions; 178 duplications) ranging from 600 to 7820 kbp. According to the ClinVar database, 137 CNVs (60.89%) were fully overlapping with previously annotated variants, 66 CNVs (29.33%) were in partial overlap, and 22 CNVs (9.78%) did not overlap with any previously described variant. Identified variants were further classified with the AnnotSV method. In summary, we identified 129 likely benign variants, 13 variants of uncertain significance, and 83 likely pathogenic variants. In this study, we use NIPT as a valuable source of population specific data. Our results suggest the utility of genomic data from commercial CNV analysis test as background for a population study. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.},
keywords = {Copy number variation, Non-invasive prenatal testing, Population study},
pubstate = {published},
tppubtype = {article}
}
Copy number variants (CNVs) are an important type of human genome variation, which play a significant role in evolution contribute to population diversity and human genetic diseases. In recent years, next generation sequencing has become a valuable tool for clinical diagnostics and to provide sensitive and accurate approaches for detecting CNVs. In our previous work, we described a non-invasive prenatal test (NIPT) based on low-coverage massively parallel whole-genome sequencing of total plasma DNA for detection of CNV aberrations ≥600 kbp. We reanalyzed NIPT genomic data from 5018 patients to evaluate CNV aberrations in the Slovak population. Our analysis of autosomal chromosomes identified 225 maternal CNVs (47 deletions; 178 duplications) ranging from 600 to 7820 kbp. According to the ClinVar database, 137 CNVs (60.89%) were fully overlapping with previously annotated variants, 66 CNVs (29.33%) were in partial overlap, and 22 CNVs (9.78%) did not overlap with any previously described variant. Identified variants were further classified with the AnnotSV method. In summary, we identified 129 likely benign variants, 13 variants of uncertain significance, and 83 likely pathogenic variants. In this study, we use NIPT as a valuable source of population specific data. Our results suggest the utility of genomic data from commercial CNV analysis test as background for a population study. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.