Application of Novel Next Generation Sequencing Gene Panel Assay to Genetic and Clinical Diagnosis of Inherited Bone Marrow Failure Syndromes
Notice bibliographique
Résumé
Abstract Background and Objectives. Phenotypic overlap among the inherited bone marrow failure syndromes (IBMFSs) frequently limits the ability to establish a diagnosis based solely on clinical manifestations. Since a large number of IBMFS genes (>70) have been identified, genetic testing is often prolonged and costly. Correct diagnosis, care and counseling often depend on identifying the mutated gene. Thus time-efficient and cost-effective strategies for genetic testing are essential. The aims of this study were to develop and evaluate the application of a next generation sequencing (NGS) IBMFS Gene Panel assay for genetic testing of patients with previously characterized categories of IBMFSs (e.g. Fanconi anemia and Diamond Blackfan anemia) but unknown genotype, as well as patients with unclassified IBMFSs. Methods. We designed a NGS assay to test a comprehensive panel of 72 known IBMFS genes. Genomic DNA from patients enrolled on the Canadian Inherited Marrow Failure Registry was analyzed using the Haloplex technology and Illumina Seq2000 platform. The average gene coverage was 99.12%. SureCall program was used to align, map, and identify variants. Polyphen, Sift and MutationTaster were used to predict the effect of variants on the protein. Human Splicing Finder program was used to analyze effect of splicing. The assay was validated by detecting all 50 mutations and polymorphic variants that were previously found by Sanger sequencing in 31 patients. Results. A total of 158 patients with unknown mutations were studied. Among 75 patients with known categories of IBMFSs but unknown genotypes, we found deleterious mutations in 43 patients (57.3%). These categories included Diamond Blackfan anemia, Fanconi anemia, dyskeratosis congenita, Shwachman-Diamond syndrome, TAR syndrome, familial thrombocytopenia and Kostmann/severe congenital neutropenia. Among 83 patients with unclassified IBMFSs, we found deleterious mutations and established the diagnosis in 16 patients (19.2%). Established diagnoses included dyskeratosis congenita, Diamond-Blackfan anemia, myelokathexis, GATA2-associated familial MDS, WAS-associated severe congenital neutropenia, G6PC3-associated severe congenital neutropenia, MYH9-associated disorder, MASTL-associated disorder and Wiskott-Aldrich syndrome. All identified mutations were validated. The assay allowed identification of mutant genes that had not been previously reported to be associated with the patient phenotypes in two cases. The assay led to amendment of established diagnoses in two other cases. The assay results directed a change in clinical care in multiple cases, including implementation of cancer surveillance program and consideration for prenatal diagnosis. The cost of the NGS was $470/patient compared to $4643/patient among those who underwent genetic testing by Sanger sequencing during the tenure of the study. Conclusion. Our novel assay is a rapid, accurate, and cost saving strategy for genetic investigation of patients with IBMFSs. It can identify mutations in classified and unclassified IBMFSs with high level of sensitivity and precision. Disclosures No relevant conflicts of interest to declare.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».