Correlation of Telomere Length in Blood, Buccal Cells, and Fibroblasts From Patients with Inherited Bone Marrow Failure Syndromes.
Notice bibliographique
Résumé
Abstract Abstract 1083 Poster Board I-105 Introduction Patients with dyskeratosis congenita (DC), an inherited bone marrow failure syndrome (IBMFS), have defects in telomere biology. Measurement of telomere length (TL) by flow fluorescence in situ hybridization (FISH) in white blood cell (WBC) subsets is a very important diagnostic tool in DC. Quantitative PCR (Q-PCR) is a high-throughput method of TL measurement that is currently used in large epidemiologic studies. It measures telomere length as a ratio of TTAGGG repeat copy number to a single copy gene number (T/S), and is often used on DNA derived from blood or buccal cells. There are limited data on tissue-specific correlations of TL and on the comparability of studies using different methods. In order to better understand tissue TL variability, we evaluated intra-individual correlations of DNA extracted from frozen blood, fibroblasts, and buccal cells by Q-PCR; and flow-FISH TL in WBC subsets. Patients and Methods We studied 21 patients: 5 Diamond-Blackfan Anemia (DBA), 6 DC, 5 Fanconi anemia (FA), and 4 Shwachman-Diamond Syndrome (SDS), enrolled in the National Cancer Institute's IBMFS study who contributed blood, buccal cells, and fibroblasts, and also had WBC flow-FISH TL measured. Genomic DNA was extracted from either whole blood (n=4) or the WBC pellet remaining after ficoll separation (n=17, primarily granulocytes) by manual Gentra Puregene. DNA was isolated from fibroblasts and buccal cells by phenol-chloroform extraction. TL was measured by Q-PCR of DNA from the three tissue types, and by flow-FISH in WBC subsets (lymphocytes and cell types matched to the types of WBC used in DNA extraction). We used the Wilcoxon signed-rank test to compare the median ranks of paired TL, and Spearman rank correlation coefficient to measure the strength of the associations between these measurements. Results TL in patients with DC was significantly (p<0.01) shorter than in patients with other IBMFS in all Q-PCR measurements of DNA from blood, fibroblasts, buccal cells; and flow-FISH WBC lymphocytes and matched cell types of WBC used in DNA extraction (86% were from granulocytes). Across all disorders, the median Q-PCR TL was longer in fibroblast and buccal cell DNA when compared with peripheral blood DNA (overall T/S ratio= 1.42 and 1.16 vs. 1.05, p=0.0002, 0.002, respectively). Although the absolute values varied, we observed in all IBMFS overall statistically significant (p≤0.001) intra-individual correlations in TL measured by Q-PCR in blood and fibroblast (r=0.67), blood and buccal cells (r=0.77), as well as fibroblast and buccal cells (r=0.67). When stratifying by disease subtype, statistically significant (p<0.05) correlations of Q-PCR in blood and buccal cells (r=0.9), and fibroblast and buccal cells (r=0.9) were observed in DC, and Q-PCR in blood and fibroblasts (r=1.0) in SDS. None of the Q-PCR tissue correlations reached statistical significance in FA or DBA. In addition, overall statistically significant (p≤0.01) correlations between TL in flow-FISH WBC subsets and Q-PCR in blood, fibroblast and buccal cells were observed. The correlations were driven mainly by the correlations with Q-PCR in blood and buccal cells in DC patients and with Q-PCR in fibroblasts in SDS patients. Conclusions Overall Q-PCR TL was correlated between blood, buccal cells and fibroblasts and in comparison with flow-FISH TL, but there was some variability within different IBMFS. The poor correlation between tissues in FA and DBA might reflect blood-specific TL attrition in response to bone marrow stress. Most important, the correlation profile observed in DC suggests that the heritability of TL in DC is tissue independent. Blood or tissue Q-PCR TL appear to be useful in identifying individuals with DC who are unable to provide a fresh blood sample (e.g. epidemiologic studies or patients after bone marrow transplantation), although larger studies are needed to confirm or refute these findings. When possible, flow-FISH TL in subsets of leukocytes remains the modality of choice for the diagnosis of DC. Disclosures Lansdorp: Repeat Diagnostics Inc.: Equity Ownership.
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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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,001 | 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 ».