DNA copy-number analysis in bipolar disorder and schizophrenia reveals aberrations in genes involved in glutamate signaling
Bibliographic record
Abstract
Using bacterial artificial chromosome (BAC) array comparative genome hybridization (aCGH) at approximately 1.4 Mbp resolution, we screened post-mortem brain DNA from bipolar disorder cases, schizophrenia cases and control individuals (n=35 each) for DNA copy-number aberrations. DNA copy number is a largely unexplored source of human genetic variation that may contribute risk for complex disease. We report aberrations at four loci which were seen in affected but not control individuals, and which were verified by quantitative real-time PCR. These aberrant loci contained the genes encoding EFNA5, GLUR7, CACNG2 and AKAP5; all brain-expressed proteins with known or postulated roles in neuronal function, and three of which (GLUR7, CACNG2 and AKAP5) are involved in glutamate signaling. A second cohort of psychiatric samples was also tested by quantitative PCR using the primer/probe sets for EFNA5, GLUR7, CACNG2 and AKAP5, and samples with aberrant copy number were found at three of the four loci (GLUR7, CACNG2 and AKAP5). Further scrutiny of these regions may reveal insights into the etiology and genetic risk factors for these complex 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 | 0.000 |
| 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) | 0.001 | 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".