Telomere length is associated with disease severity and declines with age in dyskeratosis congenita
Bibliographic record
Abstract
BACKGROUND: Dyskeratosis congenita is a cancer-prone bone marrow failure syndrome caused by aberrations in telomere biology. DESIGN AND METHODS: We studied 65 patients with dyskeratosis congenita and 127 unaffected relatives. Telomere length was measured by automated multicolor flow fluorescence in situ hybridization in peripheral blood leukocyte subsets. We age-adjusted telomere length using Z-scores (standard deviations from the mean for age). RESULTS: We confirmed that telomere lengths below the first percentile for age are very sensitive and specific for the diagnosis of dyskeratosis congenita. We provide evidence that lymphocytes alone and not granulocytes may suffice for clinical screening, while lymphocyte subsets may be required for challenging cases, including identification of silent carriers. We show for the first time using flow fluorescence in situ hybridization that the shortest telomeres are associated with severe variants (Hoyeraal-Hreidarsson and Revesz syndromes), mutations in DKC1, TINF2, or unknown genes, and moderate or severe aplastic anemia. In the first longitudinal follow up of dyskeratosis congenita patients, we demonstrate that telomere lengths decline with age, in contrast to the apparent stable telomere length observed in cross-sectional data. CONCLUSIONS: Telomere length by flow fluorescence in situ hybridization is an important diagnostic test for dyskeratosis congenita; age-adjusted values provide a quantitative measure of disease severity (clinical subset, mutated gene, and degree of bone marrow failure). Patients with dyskeratosis congenita have accelerated telomere shortening. This study is registered at www.clinicaltrials.gov (identifier: NCT00027274).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".