Improving the diagnostics of rare lung disorders using a uniquely designed pipeline for analysis of ngs data
Аутори
Anđelković, MarinaSkakić, Anita
Stevanović, Nina
Parezanović, Marina
Komazec, Jovana
Klaassen, Kristel
Spasovski, Vesna
Stojiljković, Maja
Pavlović, Sonja
Конференцијски прилог (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
Rare lung diseases (RLDs) are a group of diseases that individually affect one in 2,000 people, with an
estimate that about 80% of RLDs have a genetic origin. Despite the variations among RLDs in clinical
characteristics and manifestations, most of these diseases similarly damage the lungs, making diagnosis
difficult. The utility of NGS technology in RLDs for diagnostic purposes allows a better understanding
of the genetic background, however, the identification and classification of disease-causing variants are
challenging. Further, numerous VUS (variants of uncertain significance) that cannot be precisely
defined and classified are produced. The main goal of this study was to create a unique guideline that
will enable the standardization of the assessment of novel genetic variants in RLDs causative genes.
The designed pipeline consists of three main steps: (1) sequencing, detection, and identification of
genes/variants, (2) classification of variants, and (3) characterizatio...n of variants using in silico
structural and functional analysis. The pipeline validation was performed through the analysis of
variants detected in a disease-causing and candidate genes of one of the RLDSs, and detected VUS
variants have gained diagnostic significance. The application of this pipeline resulted in the
identification and classification of novel variants, through analysis at the transcriptional, translational,
and posttranslational levels, and led to accurate diagnosis.
Кључне речи:
pipeline / rare lung diseases (RLDs) / classification of variants / characterization of variants / sequencing / detection / identification of genes/variantsИзвор:
Genetics & Applications, 2023, 7, 2 (Special edition), 104-Издавач:
- Sarajevo : Institute for Genetic Engineering and Biotechnology, University of Sarajevo
Напомена:
- Book of abstracts: International Conference of Biochemists and Molecular Biologists in Bosnia and Herzegovina - ABMBBIH May, 2023
Колекције
Институција/група
Institut za molekularnu genetiku i genetičko inženjerstvoTY - CONF AU - Anđelković, Marina AU - Skakić, Anita AU - Stevanović, Nina AU - Parezanović, Marina AU - Komazec, Jovana AU - Klaassen, Kristel AU - Spasovski, Vesna AU - Stojiljković, Maja AU - Pavlović, Sonja PY - 2023 UR - https://imagine.imgge.bg.ac.rs/handle/123456789/1900 AB - Rare lung diseases (RLDs) are a group of diseases that individually affect one in 2,000 people, with an estimate that about 80% of RLDs have a genetic origin. Despite the variations among RLDs in clinical characteristics and manifestations, most of these diseases similarly damage the lungs, making diagnosis difficult. The utility of NGS technology in RLDs for diagnostic purposes allows a better understanding of the genetic background, however, the identification and classification of disease-causing variants are challenging. Further, numerous VUS (variants of uncertain significance) that cannot be precisely defined and classified are produced. The main goal of this study was to create a unique guideline that will enable the standardization of the assessment of novel genetic variants in RLDs causative genes. The designed pipeline consists of three main steps: (1) sequencing, detection, and identification of genes/variants, (2) classification of variants, and (3) characterization of variants using in silico structural and functional analysis. The pipeline validation was performed through the analysis of variants detected in a disease-causing and candidate genes of one of the RLDSs, and detected VUS variants have gained diagnostic significance. The application of this pipeline resulted in the identification and classification of novel variants, through analysis at the transcriptional, translational, and posttranslational levels, and led to accurate diagnosis. PB - Sarajevo : Institute for Genetic Engineering and Biotechnology, University of Sarajevo C3 - Genetics & Applications T1 - Improving the diagnostics of rare lung disorders using a uniquely designed pipeline for analysis of ngs data IS - 2 (Special edition) SP - 104 VL - 7 UR - https://hdl.handle.net/21.15107/rcub_imagine_1900 ER -
@conference{ author = "Anđelković, Marina and Skakić, Anita and Stevanović, Nina and Parezanović, Marina and Komazec, Jovana and Klaassen, Kristel and Spasovski, Vesna and Stojiljković, Maja and Pavlović, Sonja", year = "2023", abstract = "Rare lung diseases (RLDs) are a group of diseases that individually affect one in 2,000 people, with an estimate that about 80% of RLDs have a genetic origin. Despite the variations among RLDs in clinical characteristics and manifestations, most of these diseases similarly damage the lungs, making diagnosis difficult. The utility of NGS technology in RLDs for diagnostic purposes allows a better understanding of the genetic background, however, the identification and classification of disease-causing variants are challenging. Further, numerous VUS (variants of uncertain significance) that cannot be precisely defined and classified are produced. The main goal of this study was to create a unique guideline that will enable the standardization of the assessment of novel genetic variants in RLDs causative genes. The designed pipeline consists of three main steps: (1) sequencing, detection, and identification of genes/variants, (2) classification of variants, and (3) characterization of variants using in silico structural and functional analysis. The pipeline validation was performed through the analysis of variants detected in a disease-causing and candidate genes of one of the RLDSs, and detected VUS variants have gained diagnostic significance. The application of this pipeline resulted in the identification and classification of novel variants, through analysis at the transcriptional, translational, and posttranslational levels, and led to accurate diagnosis.", publisher = "Sarajevo : Institute for Genetic Engineering and Biotechnology, University of Sarajevo", journal = "Genetics & Applications", title = "Improving the diagnostics of rare lung disorders using a uniquely designed pipeline for analysis of ngs data", number = "2 (Special edition)", pages = "104", volume = "7", url = "https://hdl.handle.net/21.15107/rcub_imagine_1900" }
Anđelković, M., Skakić, A., Stevanović, N., Parezanović, M., Komazec, J., Klaassen, K., Spasovski, V., Stojiljković, M.,& Pavlović, S.. (2023). Improving the diagnostics of rare lung disorders using a uniquely designed pipeline for analysis of ngs data. in Genetics & Applications Sarajevo : Institute for Genetic Engineering and Biotechnology, University of Sarajevo., 7(2 (Special edition)), 104. https://hdl.handle.net/21.15107/rcub_imagine_1900
Anđelković M, Skakić A, Stevanović N, Parezanović M, Komazec J, Klaassen K, Spasovski V, Stojiljković M, Pavlović S. Improving the diagnostics of rare lung disorders using a uniquely designed pipeline for analysis of ngs data. in Genetics & Applications. 2023;7(2 (Special edition)):104. https://hdl.handle.net/21.15107/rcub_imagine_1900 .
Anđelković, Marina, Skakić, Anita, Stevanović, Nina, Parezanović, Marina, Komazec, Jovana, Klaassen, Kristel, Spasovski, Vesna, Stojiljković, Maja, Pavlović, Sonja, "Improving the diagnostics of rare lung disorders using a uniquely designed pipeline for analysis of ngs data" in Genetics & Applications, 7, no. 2 (Special edition) (2023):104, https://hdl.handle.net/21.15107/rcub_imagine_1900 .