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or more independent studies in schizophrenia along with a series of expanded meta-analyses incorporating published and unpublished genome-wide association (GWA) study data.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 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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".