Cholinergic system in schizophrenia: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Studies have shown widespread alterations in different components of the cholinergic system in schizophrenia, but to date the evidence has not been systematically reviewed and summarized. Here, we systematically review imaging and post-mortem studies on the central cholinergic system in schizophrenia/schizoaffective disorder. SUBJECTS/METHODS: Searches were performed in Embase and Medline. Study designs included cross-sectional case control studies comparing individuals with schizophrenia/schizoaffective disorder to control population. Risk of bias was assessed with the NIH/NHLBI tool for Quality Assessment of Case-Control Studies. The current study followed the PRISMA 2020 guidelines (PROSPERO: CRD42023402126). RESULTS: A total of 3259 studies were screened and 61 met eligibility criteria for the systematic review, including 8 in vivo neuroimaging and 53 post-mortem studies. About 74% of these studies described significant alterations, most often reductions in either muscarinic or nicotinic receptor levels in schizophrenia. We also conducted 3 meta-analyses showing reductions in M1/M4 muscarinic receptors in the striatum (g = -0.809, k = 3, n = 108), hippocampus (g = -0.872, k = 3, n = 84), and fronto-cingulate cortex (g = -0.438, k = 4, n = 295). Six neuroimaging studies reported associations with clinical symptom severity measures, and four investigations with cognitive dysfunction. CONCLUSIONS: Our review demonstrates a widespread decrease in muscarinic and nicotinic receptor levels in schizophrenia, evident in both neuroimaging and post-mortem studies. Our meta-analyses show large to moderate effects for the reductions in M1/M4 muscarinic receptors in the striatum, hippocampus, and fronto-cingulate cortex. Limitations and future directions for the field are discussed.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".