Childhood Maltreatment and Leukocyte Telomere Length: Cardiac Vagal Activity Influences the Relation in Older Adults
Bibliographic record
Abstract
OBJECTIVE: Childhood maltreatment is associated with shorter leukocyte telomere length (LTL). However, the influence of cardiac vagal control on this relation is unknown. We examined whether cardiac vagal control at rest and in response to stress moderates or cross-sectionally mediates the relationship between childhood maltreatment and LTL. METHODS: Participants were 1179 men and women (aged 65 [7.2] years) suffering from coronary artery disease or non-cardiovascular chronic disease. They completed a childhood maltreatment questionnaire and underwent a stress protocol while electrocardiogram was monitored. High-frequency heart rate variability (HF-HRV) measures were obtained at rest, during stress, and after stress in absolute and normalized units (nu). LTL was measured using quantitative polymerase chain reaction. Mediation and moderation analyses were performed. RESULT: HF-HRV and HF-HRV in normalized units (HFnu) measures did not mediate the childhood maltreatment-LTL relation. However, baseline HFnu ( p = .027) and HFnu reactivity ( p = .051) moderated the relation. Specifically, maltreatment was associated with significantly lower LTL among those with baseline HFnu at ( b = -0.059, p = .003) or below the mean ( b = -0.103, p < .001), but not among those with higher baseline HFnu. It was also associated with significantly lower LTL among participants who showed either blunted ( b = -0.058, p = .004) or increased HFnu ( b = -0.099, p = .001) responses to stress but not in those with large decreases in HFnu. CONCLUSIONS: Childhood maltreatment was associated with lower LTL in those who showed a distinct cardiac vagal profile at baseline and in response to stress. The mechanisms and implications remain to be determined.
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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 | 0.000 | 0.000 |
| 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".