Telomere shortening in late‐life depression: A potential marker of depression severity
Bibliographic record
Abstract
OBJECTIVES: Telomeres are structures at the extremity of chromosomes that prevents genomic instability, and its shortening seems to be a hallmark of cellular aging. Past studies have shown contradictory results of telomere length (TL) in major depression, and are a few studies in late-life depression (LLD). This explores the association between TL as a molecular marker of aging and diagnosis of LLD, the severity of depressive symptoms, and cognitive performance in older adults. METHODS/DESIGN: We included 78 older adults (45 with LLD and 33 nondepressed controls, according to DSM-V criteria), aged 60-90 years. TL was measured in leukocytes by a quantitative polymerase chain reaction, determining the relative ratio (T/S) between the telomere region copy number (T) and a single copy gene (S), using a relative standard curve. RESULTS: TL was significantly shorter in the LLD compared with control participants (p = .039). Comparing groups through the severity of depressive symptoms, we found a negative correlation with the severity of depressive symptoms (Hamilton Depression Rating Scale-21, r = -0.325, p = .004) and medical burden (r = -0.271, p = .038). There was no significant correlation between TL and cognitive performance (Mattis Dementia Rating Scale, r = 0.152, p = .21). CONCLUSIONS: We found that older adults with LLD have shorter telomere than healthy controls, especially those with a more severe depressive episode. Our findings suggest that shorter TL can be a marker of the severity of depressive episodes in older adults and indicate that these individuals may be at higher risk of age-associated adverse outcomes linked to depression.
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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 | 0.002 |
| 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".