Identification and functional characterization of 2 variant alleles of the telomerase RNA template gene (TERC) in a patient with dyskeratosis congenita
Bibliographic record
Abstract
Heterozygous mutations of the human telomerase RNA template gene (TERC) have been described in patients with acquired aplastic anemia and the autosomal dominant form of dyskeratosis congenita (DKC). Patients with mutations in both TERC alleles have not yet been reported. Here, we report a patient with DKC who inherited 2 distinct TERC sequence variants from her parents; a deletion (216_229del) in one and a point mutation (37A>G) in the other allele of the TERC gene. Her marrow was hypocellular and showed an abnormal clone [46, XX t(7;21)(q34;q22)]. The telomere lengths in leukocytes of the patient and her relatives were shorter than those of the age-matched controls and were progressively shorter in subsequent generations of family members with the 216_229del allele. Telomerase enzymatic levels in lymphocytes from the patient were approximately half of those measured in healthy controls. The 216_229del mutation failed to reconstitute telomerase activity in transfected cells, but, when coexpressed with the 37A>G variant, telomerase activity was only modestly suppressed. These clinical and laboratory findings support the concept that telomerase levels in human hematopoietic stem cells are tightly controlled as even moderately reduced levels result in accelerated telomere shortening and eventual marrow failure.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".