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Enregistrement W2563965053 · doi:10.1182/blood.v126.23.2416.2416

Copy Number Variants Underlying Inherited Bone Marrow Failure Syndromes

2015· article· en· W2563965053 sur OpenAlexaffabout
Nicolas Waespe, Santhosh Dhanraj, Manju Wahala, Tom Enbar, Bozana Zlateska, Hongbing Li, Robert J. Klaassen, Conrad V. Fernandez, Rochelle Yanofsky, John K. Wu, Yves Pastore, Mariana Silva, Jeffrey H. Lipton, Josée Brossard, Bruno Michon, Sharon Abish, MacGregor Steele, Roona Sinha, Mark Belletrutti, Vicky R. Breakey, Lawrence Jardine, Lisa Goodyear, Liat Kofler, Ibrahim Ghemlas, Michaela Cada, Lillian Sung, Mary Shago, Stephen W. Scherer, Yigal Dror

Notice bibliographique

RevueBlood · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensJaneway Children's Health and Rehabilitation CentreLondon Health Sciences CentreMcMaster UniversityUniversity of AlbertaCentre hospitalier universitaire de QuébecCentre Hospitalier Universitaire de SherbrookeCentre Hospitalier Universitaire Sainte-JustineCancerCare ManitobaPopulation Health Research InstituteChildren's Hospital of Eastern OntarioBC Children's HospitalRoyal University HospitalMontreal Children's HospitalUniversity of TorontoSickKids FoundationPrincess Margaret Cancer CentreKingston General HospitalUniversity of ManitobaAlberta Children's HospitalIzaak Walton Killam Health CentreHospital for Sick Children
Organismes subventionnairesnon disponible
Mots-clésCopy-number variationExact testSNP arrayGeneticsBiologyGenotypeGenotype-phenotype distinctionGenetic testingBone marrow failureSNPCopy number analysisSingle-nucleotide polymorphismBioinformaticsMedicineGeneGenomeInternal medicineHaematopoiesis

Résumé

récupéré en direct d'OpenAlex

Abstract Background. Inherited bone marrow failure syndromes (IBMFSs) comprise a genetically heterogeneous group of diseases with hematopoietic failure and varying degrees of physical malformations. The diagnosis of an IBMFS and categorizing the specific syndrome critically impact on clinical care; however, these are commonly challenging and rely on genetic testing. Since over 80 genes have been associated with IBMFSs and might be affected by different types of DNA aberrations, the best strategy to establish a diagnosis in a timely and cost effective manner is unknown. The aims of this study were to evaluate the role of genome-wide copy number variant (CNV) analysis in unraveling causal genetic alterations in IBMFS patients with unknown genotype and determine whether correlation exists between large CNVs and more severe phenotype. Methods. Patients from the Canadian Inherited Marrow Failure Registry (CIMFR) who were genetically investigated were included in this analysis. Genetic and clinical data were extracted and analyzed. Mann-Whitney test and Fisher's exact test were used to assess statistical significance. Results. Among 328 patients from the CIMFR who underwent molecular investigation, a causal genotype was identified in 185 cases (56.4%). 69 patients had genome-wide CNV analysis by SNP/CGH arrays, among which ten (14.5%) had positive results. In four out of ten cases who were genotyped by SNP/CGH array, genome-wide CNV analysis was critical for establishing the diagnosis. Among 308 patients who were tested for nucleotide-level mutations by either targeted gene analysis or next generation sequencing panels, casual mutations were found in 169 (54.9%). Three patients had compound heterozygosity for a CNV and nucleotide-level mutation. To determine whether large deletions are correlated with more severe phenotype we included nine additional patients with causal CNVs whose genotype was identified by MLPA (n=1), targeted FISH (n=1), DNA-qPCR analysis (n=1), Southern blotting (n=1) or metaphase cytogenetics (n=5). The causal CNVs among patients in our cohort ranged from 0.02 to 145.5 Mb in size. The most common disease associated with causal CNVs was Diamond-Blackfan anemia (four patients). Patients with CNVs tended to have significantly more non-hematological organ system involvement (p=0.03), developmental delay (mean=56% vs. 28%, p=0.03) and short stature (mean=67% vs. 40%, p=0.04) than patients with nucleotide-level mutations. The difference remained significant when we compared all patients with mutations that are predicted to result in truncation or lack of protein from the respective allele (large CNV, nonsense, and indel/ frameshift) to patients with mutations that are predicted to be hypomorphic or affect function (splicing, indel/ inframe and missense). There was no correlation between CNVs and the severity of the hematological disease. Conclusions. Most patients with IBMFSs have nucleotide-level mutations. However, a significant proportion of patients without such mutations have large CNVs that are not efficiently detected by current nucleotide-level testing methods. Therefore, genome-wide CNV analysis should be considered in IBMFS cases, where nucleotide-level sequencing does not reveal the causal mutation. Patients with IBMFSs and large CNVs had more non-hematological organ system involvement, a higher prevalence of developmental delay and short stature. This might be related to an additional impact of the CNVs on other genes close to the affected IBMFS gene or the severe damaging effect of the CNVs. Disclosures Lipton: Teva: Consultancy, Research Funding; Ariad: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Novartis Pharmaceuticals: Consultancy, Research Funding.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,042
Score d'incertitude au seuil0,083

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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.

Tête enseignante Opus0,068
Tête enseignante GPT0,331
Écart entre enseignants0,262 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission2
Résumé présentoui

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