New findings in pharmacogenetics of schizophrenia
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review highlights recent advances in the investigation of genetic factors for antipsychotic response and side effects. RECENT FINDINGS: Antipsychotics prescribed to treat psychotic symptoms are variable in efficacy and propensity for causing side effects. The major side effects include tardive dyskinesia, antipsychotic-induced weight gain (AIWG), and clozapine-induced agranulocytosis (CIA). Several promising associations of polymorphisms in genes including HSPG2, CNR1, and DPP6 with tardive dyskinesia have been reported. In particular, a functional genetic polymorphism in SLC18A2, which is a target of recently approved tardive dyskinesia medication valbenazine, was associated with tardive dyskinesia. Similarly, several consistent findings primarily from genes modulating energy homeostasis have also been reported (e.g. MC4R, HTR2C). CIA has been consistently associated with polymorphisms in the HLA genes (HLA-DQB1 and HLA-B). The association findings between glutamate system genes and antipsychotic response require additional replications. SUMMARY: The findings to date are promising and provide us a better understanding of the development of side effects and response to antipsychotics. However, more comprehensive investigations in large, well characterized samples will bring us closer to clinically actionable findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".