Psychological Profiles in the Prediction of Leukocyte Telomere Length in Healthy Individuals
Bibliographic record
Abstract
BACKGROUND: Shorter telomere length (TL) may signal premature cellular aging and increased risk for disease. While depression and psychosocial stress have been associated with shorter telomeres, other psychological risk factors for cardiovascular disease have received less attention. PURPOSE: To evaluate the association between TL and psychological risk factors (symptoms of anxiety and depression, hostility and defensiveness traits) for heart disease, and to examine whether chronological age and sex moderate the associations observed. METHODS: 132 healthy men and women (Mage = 45.34 years) completed the Marlowe-Crowne Social Desirability Scale, the Beck Depression Inventory II, The Beck Anxiety Inventory and the Cook-Medley Hostility Scale. Relative TL was measured by quantitative polymerase chain reaction (PCR) of total genomic DNA samples. A series of hierarchical linear regressions were performed controlling for pertinent covariates. RESULTS: Shorter TL was observed among individuals high in defensiveness (β = -.221) and depressive symptoms (β = -.213), as well as in those with less hostility (β =.256) and anxiety (β =.220)(all Ps<.05). Psychological variables explained 19% of the variance over and above that explained by covariates (age, sex, exercise, alcohol consumption, systemic inflammation, and 24-hr mean arterial pressure). Age moderated the relation between TL and defensiveness (β =.179, p =.03). Sex did not influence any of the relations. CONCLUSIONS: Telomere length is associated with psychological burden though the direction of effect differs depending on the psychological variables under study. Further research is needed to determine the reasons for and implications of these seemingly contradictory findings.
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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 | 0.001 | 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".