Serine racemase is associated with schizophrenia susceptibility in humans and in a mouse model
Bibliographic record
Abstract
Abnormal N-methyl-d-aspartate receptor (NMDAR) function has been implicated in the pathophysiology of schizophrenia. d-serine is an important NMDAR modulator, and to elucidate the role of the d-serine synthesis enzyme serine racemase (Srr) in schizophrenia, we identified and characterized mice with an ENU-induced mutation that results in a complete loss of Srr activity and dramatically reduced d-serine levels. Mutant mice displayed behaviors relevant to schizophrenia, including impairments in prepulse inhibition, sociability and spatial discrimination. Behavioral deficits were exacerbated by an NMDAR antagonist and ameliorated by d-serine or the atypical antipsychotic clozapine. Expression profiling revealed that the Srr mutation influenced several genes that have been linked to schizophrenia and cognitive ability. Transcript levels altered by the Srr mutation were also normalized by d-serine or clozapine treatment. Furthermore, analysis of SRR genetic variants in humans identified a robust association with schizophrenia. This study demonstrates that aberrant Srr function and diminished d-serine may contribute to schizophrenia pathogenesis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.003 | 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".