The schizophrenia genetics knowledgebase: a comprehensive update of findings from candidate gene studies
Bibliographic record
Abstract
Over 3000 candidate gene association studies have been performed to elucidate the genetic underpinnings of schizophrenia. However, a comprehensive evaluation of these studies' findings has not been undertaken since the decommissioning of the schizophrenia gene (SzGene) database in 2011. As such, we systematically identified and carried out random-effects meta-analyses for all polymorphisms with four or more independent studies in schizophrenia along with a series of expanded meta-analyses incorporating published and unpublished genome-wide association (GWA) study data. Based on 550 meta-analyses, 11 SNPs in eight linkage disequilibrium (LD) independent loci showed Bonferroni-significant associations with schizophrenia. Expanded meta-analyses identified an additional 10 SNPs, for a total of 21 Bonferroni-significant SNPs in 14 LD-independent loci. Three of these loci (MTHFR, DAOA, ARVCF) had never been implicated by a schizophrenia GWA study. In sum, the present study has provided a comprehensive summary of the current schizophrenia genetics knowledgebase and has made available all the collected data as a resource for the research community.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".