Telomere Length, Oxidative Stress, Inflammation and BDNF Levels in Siblings of Patients with Bipolar Disorder: Implications for Accelerated Cellular Aging
Bibliographic record
Abstract
Background: Growing evidence supports the existence of neurobiological trait abnormalities in individuals at genetic risk for bipolar disorder. The aim of this study was to examine potential differences in brain-derived neurotrophic factor, cytokines, oxidative stress, and telomere length markers between patients with bipolar disorder, their siblings, and healthy controls. Methods: Thirty-six patients with bipolar disorder type I, 39 siblings, and 44 healthy controls were assessed. Serum levels of brain-derived neurotrophic factor, interleukin-6, interleukin-10, tumor necrosis factor-α, C-C motif chemokine 11, C-C motif chemokine 24, and 3-nitrotyrosine were measured, as were the activities of glutathione peroxidase, glutathione reductase, and glutathione S-transferase. Telomere length (T/S ratio) was measured using quantitative polymerase chain reaction. Results: Telomere length was different between the 3 groups (P = .041) with both patients and siblings showing a shorter T/S ratio compared with healthy controls. Patients showed increased levels of interleukin-6 (P = .005) and interleukin-10 (P = .002) compared with controls as well as increased levels of interleukin-6 (p = 0.014) and CCL24 (P = .016) compared with their siblings. C-C motif chemokine 11 levels were increased in siblings compared with controls (P = .015), and a similar tendency was found in patients compared with controls (P = .045). Glutathione peroxidase activity was decreased in patients compared with controls (P = .006) and siblings (P = .025). No differences were found for the other markers. Conclusions: The present results suggest that unaffected siblings may present accelerated aging features. These neurobiological findings may be considered as endophenotypic traits. Further prospective studies are warranted.
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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 | 0.000 | 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".