Molecular Analysis of Diamond Blackfan Anemia and Genotype-Phenotype Correlation: Experience from the Canadian Inherited Marrow Failure Registry
Notice bibliographique
Résumé
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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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 | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».