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Correlation of Telomere Length in Blood, Buccal Cells, and Fibroblasts From Patients with Inherited Bone Marrow Failure Syndromes.

2009· article· en· W2979812322 on OpenAlexaff
Shahinaz M. Gadalla, Richard Cawthon, Neelam Giri, Gabriela M. Baerlocher, Peter M. Lansdorp, Blanche P. Alter, Sharon A. Savage

Bibliographic record

VenueBlood · 2009
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsTerry Fox Research Institute
Fundersnot available
KeywordsDyskeratosis congenitaBuccal swabBiologyTelomereFluorescence in situ hybridizationBuccal administrationDNA extractionMolecular biologyPathologyBone marrowPolymerase chain reactionDNAImmunologyMedicineGeneticsGeneBioinformatics

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.006
GPT teacher head0.194
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations4
Published2009
Admission routes1
Has abstractyes

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