Molecular Analysis of Diamond Blackfan Anemia and Genotype-Phenotype Correlation: Experience from the Canadian Inherited Marrow Failure Registry
Bibliographic record
Abstract
Abstract Background/Objectives: Diamond Blackfan anemia (DBA) is an inherited disorder characterized by chronic hypoproductive anemia, physical malformations, and an increased risk of malignancies. At least 12 DBA genes have been identified, which include various ribosomal protein genes and the transcription factor GATA1. The aims of our study were (1) to identify the mutation spectrum of DBA patients, utilizing a cohort of patients enrolled on the Canadian Inherited Marrow Failure Registry (CIMFR) and (2) to determine whether specific hematological abnormalities, malformations, and outcomes are associated with specific mutations. Methods: Patients were enrolled on the CIMFR, which is a multicenter cohort study of inherited bone marrow failure syndromes (IBMFS). Genetic testing was performed using one or more of the following tests: Sanger sequencing, next generation sequencing (NGS) DBA gene panel, a comprehensive NGS IBMFS gene panel developed in our laboratory, or comparative genetic hybridization (CGH). Severity of the hematological disease was dichotomized according to a patient's requirement for chronic treatment: those who were maintained on corticosteroids, blood transfusions, or received a hematopoietic stem cell transplantation were considered to have a more severe phenotype than those who did not require hematological treatment. Chi-square tests with a Fisher's exact test correction were used to compare genetic groups with at least 5 patients on observed phenotypes. Results: 71 patients with DBA have been enrolled in our registry. A causal mutation has been identified in 36 of these patients, with the following rates: RPS19 (n=11), RPL11 (n=7), RPL5 (n=6), RPS26 (n=5), RPL35a (n=2), RPS24 (n=2), and one of each RPS7, RPS29, RPS17. Remarkably, a substantial number of patients in our population-based cohort (19.4%) had mild hematological phenotype requiring no therapy. Patients with RPL11 mutations tended to have a less severe DBA phenotype, while patients with RPS19 mutations tended to have a more severe phenotype (p=0.04). In terms of non-hematological malformations, we found no differences in cardiac, stature and craniofacial malformations across the groups compared (all p>0.1). However, patients with RPL5 mutations had significantly more hand malformations (p=0.02), and patients with RPS26 mutations had more genitourinary malformations (p=0.04). To control for the impact of mutation severity on the observed phenotype, we compared the prevalence of mutations that are predicted to result in truncated or lack of protein from the respective allele (large copy-number variation, nonsense, or indel frameshift) to mutations that are predicted to be hypomorphic or affect function (splicing, indel/inframe and, missense) between mutation categories. There were no differences among genetic groups in the severity of their mutations (p=0.58). Conclusions: Mutations in a wide spectrum of ribosomal protein genes underlie DBA cases in Canada, which approximate those observed by other registries in Western countries. Patients with DBA caused by RPL11 mutations tended to have a milder hematological phenotype, while patients with RPS19 mutation tended to have a more severe phenotype. Mutations in RPS26 and RPL5 are associated with genitourinary and hand malformations, respectively. Our findings may help improve counseling of DBA patients and their family. Future studies are needed to replicate our results and determine whether these findings can help personalize care. Disclosures Lipton: Ariad: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Teva: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Novartis Pharmaceuticals: Consultancy, Research Funding.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".