Mitochondrial dysfunction in psychiatric morbidity: current evidence and therapeutic prospects
Bibliographic record
Abstract
Cumulating evidence for the involvement of mitochondrial dysfunction in psychiatric disorders leaves little to no doubt regarding the involvement of this pathology in mood disorders. However, mitochondrial abnormalities are also observed in a wide range of disorders spanning from cancer and diabetes to various neurodegenerative and neurodevelopmental disorders such as Parkinson's, Alzheimer's, Huntington's, autism, and amyotrophic lateral sclerosis. The apparent lack of specificity questions the role of mitochondrial dysfunction in psychiatric disorders, in general, and in mood disorders, in particular. Is mitochondrial dysfunction a general phenomenon, simplistically rendering brain cells to be more vulnerable to a variety of disease-specific perturbations? Or is it an epiphenomenon induced by various disease-specific factors? Or possibly, the severity and the anatomical region of the dysfunction are the ones responsible for the distinct features of the disorders. Whichever of the aforementioned ones, if any, is correct, "mitochondrial dysfunction" became more of a cliché than a therapeutic target. In this review, we summarize current studies supporting the involvement of mitochondrial dysfunction in different psychiatric disorders. We address the question of specificity and causality of the different findings and provide an alternative explanation for some of the aforementioned questions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".