Telomere Length and Reproductive Aging
Bibliographic record
Abstract
Previous studies have suggested an association between rates of biological and reproductive aging. Short telomere length is a marker for cellular aging and may occur more frequently in women with poor oocyte quality and a history of premature reproductive senescence. Telomere length, however, has been both positively and negatively associated with different measures of reproductive aging in a number of studies. In the present study, the investigators tested the hypothesis that women with a history of premature reproductive aging have a shorter average telomere length than women without such a history. Telomere length in peripheral blood leukocytes was measured in 2 groups of women with evidence of premature reproductive aging: Group 1 (n = 34) was comprised of women with idiopathic premature ovarian failure (POF) who experienced menopause before 40 years of age and group 2 (n = 95) contained women with a history of recurrent miscarriage (RM). The 2 control groups were healthy women of reproductive age from the general population (C1, n = 108) and women who had had a healthy pregnancy after 37 years of age (C2, n = 46). Telomere length was measured using telomere-specific quantitative PCR. The age-adjusted mean telomere length was shorter among women in the RM group than among those in both control groups (8.46 kb for RM vs. 8.92 kb for C1, [P = 0.0004] and 9.11 kb for C2, [P = 0.02]), respectively. However, this effect was not specifically confined to women known to have experienced trisomic pregnancies. Contrary to expectation, women in the POF group did not have a shorter age-adjusted mean telomere length than those in the controls: Telomere length in POF women was longer compared to C1 (9.58 vs. 8.92 kb, P = 0.01) and not significantly different than C2. These findings suggest that both the opposing association of RM and POF with telomere length, and lack of an association of trisomic pregnancy—as manifestations of different types of reproductive aging—may result from unique physiological factors. The results require confirmation in studies with larger and more defined patient populations.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".