Telomere Length Measurement by Flow-FISH Distinguishes Dyskeratosis Congenita from Other Bone Marrow Failure Syndromes.
Notice bibliographique
Résumé
Abstract This study was designed to evaluate the utility of flow-FISH telomere length measurement in white blood cells (WBC) as a screening test for Dyskeratosis congenita (DC). We studied 26 patients: 17 with DC, 1 silent carrier (clinically normal; mutation in TERC), 4 with the Hoyeraal-Hreidarsson variant (HH), and 4 with Revesz Syndrome. Five had mutations in DKC1, 5 in TERC, and 2 in TERT. 23 had hematologic abnormalities, 19 had 2 or 3 of the DC diagnostic triad (lacey pigmentation, dyskeratotic nails, and leukoplakia), and 4 had soft signs of DC. We evaluated 54 first-degree relatives of DC patients, 16 Fanconi Anemia patients (FA), 14 with Diamond-Blackfan Anemia (DBA), 5 with Shwachman Diamond Syndrome (SDS), and 10 with other possibly inherited cytopenias (Other). Telomere length was measured in granulocytes and lymphocyte subsets by automated multicolor flow-FISH; results were compared with age-matched values from 400 normal controls. “Very low (VL)” telomere length was defined as a mean telomere length below the normal first percentile for age and specific WBC type. We observed VL telomeres in all subsets in the silent carrier, all HH and Revesz patients, and 15/17 with DC. Eight of 51 DC relatives had VL telomeres in granulocytes versus 2/54 with VL telomeres in lymphocytes. The sensitivities for distinguishing a DC patient from an unaffected relative were 92% in lymphocytes and 96% in granulocytes; the specificities were 96% and 98%, respectively; the sensitivity and specificity for VL telomeres in both cell types were 96% and 96%. The silent carrier with a TERC mutation developed thrombocytopenia, hypocellular marrow, and a cytogenetic clone during follow-up. The 2 DC relatives with VL telomeres in lymphocytes were from a family without a known mutant gene; they may also be silent carriers. The latter possibility disqualified an HLA-matched sibling as a donor for DC-related aplastic anemia, because of engraftment concerns; another sibling donor with normal telomere length was selected. VL granulocyte telomeres were observed in 5/16 FA, 3/14 DBA, 1/5 SDS, and 1/10 Other patients, versus 2/16 FA, 1/14 DBA, 1/5 SDS, and 0/10 Other in lymphocytes, and in both lineages in only 1 each of FA, DBA, and SDS. The sensitivity and specificity for distinguishing DC from non-DC patients using VL telomeres in both lineages were 96% and 93%, respectively. Only DC patients had consistently VL telomeres in all cell subsets. Flow-FISH telomere length measurement provides a sensitive and specific method for identifying patients with DC among families, regardless of mutation status, and distinguishes patients with DC from those with other inherited or acquired marrow failure syndromes. It may also help to detect silent carriers, and facilitate identification of mutations in other telomere biology genes. Our data suggest that the diagnostic triad, soft physical findings and/or bone marrow failure may not be required for the diagnosis of DC. Correct diagnosis of DC will enhance genetic counseling and hematologic management.
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 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 | 0,000 | 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) | 0,002 | 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 ».