Novel Complex Interactions between Mitochondrial and Nuclear DNA in Schizophrenia and Bipolar Disorder
Bibliographic record
Abstract
Mitochondrial dysfunction has been associated with schizophrenia (SZ) and bipolar disorder (BD). This review examines recent publications and novel associations between mitochondrial genes and SZ and BD. Associations of nuclear-encoded mitochondrial variants with SZ were found using gene- and pathway-based approaches. Two control region mitochondrial DNA (mtDNA) SNPs, T16519C and T195C, both showed an association with SZ and BD. A review of 4 studies of A15218G located in the cytochrome B oxidase gene (CYTB, SZ = 11,311, control = 35,735) shows a moderate association with SZ (p = 2.15E-03). Another mtDNA allele A12308G was nominally associated with psychosis in BD type I subjects and SZ. The first published study testing the epistatic interaction between nuclear-encoded and mitochondria-encoded genes demonstrated evidence for potential interactions between mtDNA and the nuclear genome for BD. A similar analysis for the risk of SZ revealed significant joint effects (34 nuclear-mitochondria SNP pairs with joint effect p ≤ 5E-07) and significant enrichment of projection neurons. The mitochondria-encoded gene CYTB was found in both the epistatic interactions for SZ and BD and the single SNP association of SZ. Future efforts considering population stratification and polygenic risk scores will test the role of mitochondrial variants in psychiatric disorders.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".