Application of Novel Next Generation Sequencing Gene Panel Assay to Genetic and Clinical Diagnosis of Inherited Bone Marrow Failure Syndromes
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".