Gamma‐aminobutyric acid (GABA) levels in the midcingulate cortex and clozapine response in patients with treatment‐resistant schizophrenia: A proton magnetic resonance spectroscopy (<sup>1</sup>H‐MRS) study
Bibliographic record
Abstract
Background Gamma‐Aminobutyric Acid (GABA) is the primary inhibitory neurotransmitter in the central nervous system. GABAergic dysfunction has been implicated in the pathophysiology of schizophrenia. Clozapine, the only approved drug for treatment‐resistant schizophrenia (TRS), involves the GABAergic system as one of its targets. However, no studies have investigated the relationship between brain GABA levels, as measured by proton magnetic resonance spectroscopy (1H‐MRS), and clozapine response in patients with TRS. Methods This study enrolled patients with TRS who did not respond to clozapine (ultra‐resistant schizophrenia: URS) and who responded to clozapine (non‐URS), patients with schizophrenia who responded to first‐line antipsychotics (first‐line responders: FLR), and healthy controls (HCs). We measured GABA levels in the midcingulate cortex (MCC) using 3T1H‐MRS and compared these levels among the groups. The associations between GABA levels and symptom severity were also explored within the patient groups. Results A total of 98 participants (URS:n = 22; non‐URS:n = 25; FLR:n = 16; HCs:n = 35) completed the study. We found overall group differences in MCC GABA levels (F(3,86) = 3.25,P = 0.04). Specifically, patients with URS showed higher GABA levels compared to those with non‐URS (F(1,52) = 8.40,P = 0.03, Cohen'sd = 0.84). MCC GABA levels showed no associations with any of the symptom severity scores within each group or the entire patient group. Conclusion Our study is the first to report elevated GABA levels in the MCC in patients with schizophrenia resistant to clozapine treatment compared with those responsive to clozapine. Longitudinal studies are required to evaluate if GABA levels are a suitable biomarker to predict clozapine resistance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".