Alterations of cellular aging markers in obsessive–compulsive disorder: mitochondrial DNA copy number and telomere length
Bibliographic record
Abstract
BACKGROUND: The present study examined whether mitochondrial DNA copy number (mtDNAcn) and telomere length - key markers of cellular aging - were altered in male and female participants with obsessive-compulsive disorder (OCD) compared to healthy controls. We also tested for associations between these alterations and OCD-related clinical features and inflammatory index. METHODS: A total of 235 patients with OCD (38.7% female) and 234 healthy controls (41.5% female) were included. We quantified whole-blood mtDNAcn and leukocyte telomere length using quantitative polymerase chain reaction. We also calculated the neutrophil-to-lymphocyte ratio from complete blood cell counts. RESULTS: Multivariate analysis of covariance showed that OCD status had a significant overall effect on cellular aging markers in men (Wilks λ = 0.889, F2,275 = 17.13, p < 0.001) and women (Wilks λ = 0.742, F2,182 = 31.61, p < 0.001) after controlling for age, body mass index and childhood trauma. In post-hoc comparisons, men with OCD had lower mtDNAcn than controls (p < 0.001), but we found no between-group difference for telomere length (p = 0.55). Women with OCD had a significantly lower mtDNAcn (p < 0.001) and shortened telomere length (p = 0.023) compared to controls. Moreover, the lower mtDNAcn shown in the OCD group was significantly correlated with an increase in systemic inflammation for both sexes, as measured by neutrophil-to-lymphocyte ratio. LIMITATIONS: The present cross-sectional design did not allow us to infer a causal relationship between OCD disease status and cellular aging markers. CONCLUSION: The present study is, to our knowledge, the first to demonstrate alterations in mtDNAcn and telomere shortening in OCD. These results suggest that aging-associated molecular mechanisms may be important in the pathophysiology of OCD.
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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 | 0.001 |
| 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) | 0.002 | 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".