Low peripheral mitochondrial DNA copy number during manic episodes of bipolar disorders is associated with disease severity and inflammation
Bibliographic record
Abstract
Mitochondria (Mt) are intra-cellular components essential for cellular energy processes whose dysfunction may induce premature cellular senescence and/or inflammation, both observed in bipolar disorders (BD). We investigated mitochondrial DNA copy number (mtDNAcn) levels in patients with BD being in manic, depressive or euthymic phase and in healthy controls (HC) both characterized for the levels of blood-based inflammatory markers and stigma of pathogens. 312 patients with BD were compared to 180 HC. mtDNAcn were measured using a digital droplet PCR. Serum levels of 14 inflammatory molecules and 3 anti-infectious IgG stigma were respectively evaluated by electro-chemiluminescence, ELISA and dedicated immunoassays. The statistical analyses were performed using Spearman's correlation, Wilcoxon signed-rank and Kruskal-Wallis rank sum tests. P-values were adjusted for multiple testing with Benjamini-Hochberg method. We found low levels of mtDNAcn in BD patients as compared to HC (P = 0.008) especially during manic episodes (P = 0.0002). We also observed that low levels of mtDNAcn are negatively correlated with mood and psychotic scales (PANSS, YMRS and CGI) (adjusted P (Adj P) = 0.02, 0.003 and 0.05 respectively) and positively with the GAF severity scale (Adj P = 0.002). They were also correlated with high levels of both intercellular adhesion molecule (ICAM)-1 and vascular cell adhesion molecule (VCAM)-1 (Adj P = 0.003 and 0.001) along with a trend toward increased IL-2, IL-10 and B2M circulating levels (Adj P = 0.05). Here, we report correlations between marker of mitochondria functioning and both clinical scales and inflammatory markers in BD patients experiencing manic episodes. If replicated, these finding might allow to predict transition between disease phases and to design accurate therapeutic options.
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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".