The mitochondrial genome and psychiatric illness
Bibliographic record
Abstract
Psychiatric disorders are a leading cause of morbidity and mortality, yet their underlying pathophysiology remains unclear. Searches for a genetic cause of bipolar disorder, schizophrenia, and major depressive disorder have yielded inconclusive results. There is increasing interest in the possibility that defects in the mitochondrial genome may play an important role in psychiatric illness. We undertook a review of the literature investigating mitochondria and adult psychiatric disorders. MEDLINE, PsycINFO, and EMBASE were searched from their inception through September 2011, and the reference lists of identified articles were reviewed for additional studies. While multiple lines of evidence, including clinical, genetic, ultrastructural, and biochemical studies, support the involvement of mitochondria in the pathophysiology of psychiatric illness, many studies have methodological limitations and their findings have not been replicated. Clinical studies suggest that psychiatric features can be prominent, and the presenting features of mitochondrial disorders. There is limited but inconsistent evidence for the involvement of mitochondrial DNA haplogroups and mitochondria-related nuclear gene polymorphisms, and for mitochondrial ultrastructural and biochemical abnormalities in psychiatric illness. The current literature suggests that mitochondrial dysfunction and mitochondrial genetic variations may play an important role in psychiatric disorders, but additional methodologically rigorous and adequately powered studies are needed before definitive conclusions can be drawn.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".