Lymphocyte Telomere Length Is Long in <i>BRCA1</i> and <i>BRCA2</i> Mutation Carriers Regardless of Cancer-Affected Status
Bibliographic record
Abstract
BACKGROUND: Telomere length has been linked to risk of common diseases, including cancer, and has previously been proposed as a biomarker for cancer risk. Germline BRCA1 and BRCA2 mutations predispose to breast, ovarian, and other cancer types. METHODS: We investigated telomere length in BRCA mutation carriers and their non-carrier relatives and further examined whether telomere length is a modifier of cancer risk in mutation carriers. We measured mean telomere length in DNA extracted from whole blood using high-throughput quantitative PCR. Participants were from the EMBRACE study in United Kingdom and Eire (n = 4,822) and comprised BRCA1 (n = 1,628) and BRCA2 (n = 1,506) mutation carriers and their non-carrier relatives (n = 1,688). RESULTS: We find no significant evidence that mean telomere length is associated with breast or ovarian cancer risk in BRCA mutation carriers. However, we find mutation carriers to have longer mean telomere length than their non-carrier relatives (all carriers vs. non-carriers, Ptrend = 0.0018), particularly in families with BRCA2 mutations (BRCA2 mutation carriers vs. all non-carriers, Ptrend = 0.0016). CONCLUSIONS: Our findings lend little support to the hypothesis that short mean telomere length predisposes to cancer. Conversely, our main and unexpected finding is that BRCA mutation carriers (regardless of cancer status) have longer telomeres than their non-mutation carrier, non-cancer-affected relatives. The longer telomere length in BRCA2 mutation carriers is consistent with its role in DNA damage response. Overall, it seems that increased telomere length may be a consequence of these mutations, but is not itself directly related to the increased cancer risk in carriers. IMPACT: The finding that mutation carriers have longer mean telomere lengths than their non-carrier relatives is unexpected but biologically plausible and could open up new lines of research into the functions of the BRCA proteins. To our knowledge, this is the largest study of telomere length in BRCA mutation carriers and their relatives. The null cancer-risk association supports recent large prospective studies of breast and ovarian cancer and indicates that mean telomere length would not be a useful biomarker in these cancers. Cancer Epidemiol Biomarkers Prev; 23(6); 1018-24. ©2014 AACR.
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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 | 0.000 |
| 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) | 0.003 | 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".