An inherited duplication at the gene p21 Protein-Activated Kinase 7 (PAK7) is a risk factor for psychosis
Bibliographic record
Abstract
Identifying rare, highly penetrant risk mutations may be an important step in dissecting the molecular etiology of schizophrenia. We conducted a gene-based analysis of large (>100 kb), rare copy-number variants (CNVs) in the Wellcome Trust Case Control Consortium 2 (WTCCC2) schizophrenia sample of 1564 cases and 1748 controls all from Ireland, and further extended the analysis to include an additional 5196 UK controls. We found association with duplications at chr20p12.2 (P = 0.007) and evidence of replication in large independent European schizophrenia (P = 0.052) and UK bipolar disorder case-control cohorts (P = 0.047). A combined analysis of Irish/UK subjects including additional psychosis cases (schizophrenia and bipolar disorder) identified 22 carriers in 11 707 cases and 10 carriers in 21 204 controls [meta-analysis Cochran-Mantel-Haenszel P-value = 2 × 10(-4); odds ratio (OR) = 11.3, 95% CI = 3.7, ∞]. Nineteen of the 22 cases and 8 of the 10 controls carried duplications starting at 9.68 Mb with similar breakpoints across samples. By haplotype analysis and sequencing, we identified a tandem ~149 kb duplication overlapping the gene p21 Protein-Activated Kinase 7 (PAK7, also called PAK5) which was in linkage disequilibrium with local haplotypes (P = 2.5 × 10(-21)), indicative of a single ancestral duplication event. We confirmed the breakpoints in 8/8 carriers tested and found co-segregation of the duplication with illness in two additional family members of one of the affected probands. We demonstrate that PAK7 is developmentally co-expressed with another known psychosis risk gene (DISC1) suggesting a potential molecular mechanism involving aberrant synapse development and plasticity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".