Unit:
Faculty of MedicineLibrary of the School of Health Sciences
Author:
Tilemis Faidon-Nikolaos
Dissertation committee:
Ιωάννα-Ραχήλ Συνοδινού-Traeger, Καθηγήτρια, Ιατρική Σχολή, ΕΚΠΑ
Μαρία Τζέτη, Καθηγήτρια, Ιατρική Σχολή, ΕΚΠΑ
Χρυσταλλένα Σοφοκλέους, Επίκουρη Καθηγήτρια, Ιατρική Σχολή, ΕΚΠΑ
Αντώνιος Καττάμης, Καθηγητής, Ιατρική Σχολή, ΕΚΠΑ
Διαμάντης Σίδερης, Καθηγητής, Τμήμα Βιολογίας, ΕΚΠΑ
Περικλής Μακρυθανάσης, Επίκουρος Καθηγητής, Ιατρική Σχολή, ΕΚΠΑ
Γεώργιος Βάρτζελης, Επίκουρος Καθηγητής, Ιατρική Σχολή, ΕΚΠΑ
Original Title:
Η βελτιστοποίηση της διαγνωστικής απόδοσης της Αλληλούχησης Επόμενης Γενιάς του DNA (Next Generation Sequencing/NGS) στην Ιατρική Γενετική, μέσω βιοπληροφορικών και εργαστηριακών διαδικασιών
Translated title:
Increasing the diagnostic yield of Next Generation Sequencing (NGS) in Medical Genetics through bioinformatics and laboratory procedures
Summary:
7.000–8.000 different rare diseases (RDs) have been recognized to date, and in approximately 80% an underlying genetic cause is recognized. WES has proven to be significantly valuable in the characterization of underlying genetic defects in most RDs, reaching diagnostic yields between 30–50%; higher than any other molecular genetic method so far. Nonetheless, in about half of RD patients, a definitive molecular diagnosis may not be reached, due to inherent difficulties in identification of causative structural variants and limited experience with valid classification of single nucleotide variants (SNVs). Recent technological and bioinformatics advances have contributed to the development of efficient bioinformatics tools capable of identifying copy number variants (CNVs) and short tandem repeats (STRs) from WES data, which were initially thought to escape detection. To further improve the diagnostic yield of WES, amongst 1560 patients referred for WES to our lab, 820 unresolved cases were reanalysed, including further implementation of new and recently developed bioinformatics tools that allow the detection of CNVs and STRs from WES raw data. For CNV calling the ExomeDepth algorithm was selected, while STR detection was performed using the ExpansionHunter tool. Specifically, amongst the 820 cases, reanalysis of SNVs combined with detection of CNVs was performed in 36, reanalysis of SNVs in 84, and detection of CNVs in 700, of which in 10 STR detection was also applied. Reassessment of WES findings allowed characterization of a causative variant in 74 (in 60 CNVs and 14 SNVs), resolving 9% of cases which increased the overall diagnostic yield of WES by 4.8% {from 47.4% (740/1560) to 52.2% (814/1560)}. In addition, application of ExpansionHunter was successful in determining the exact number of repeats and STRs expansions in all 10 WES cases analyzed. Therefore, reanalysis of existing WES data increases the diagnostic yield in light of improved bioinformatics pipeline and updated literature. WES enables ancillary detection of different types of causative genetic variants by a single method, allowing characterization of diagnostic genotypes whilst concurrently minimizing the test cost to the patient/family and the time to a definitive diagnosis, and thus it should be the critical first-tier diagnostic test for patients with RDs.
Main subject category:
Health Sciences
Keywords:
Next generation sequencing, Rare genetic diseases, Bioinformatics reanalysis of genetic data, Bioinformatics algorithms, Genetic diagnosis
Number of references:
208
File:
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Tilemis_Faidon-Nikolaos_PhD.pdf
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