Dopamine receptor D3R and D4R mRNA levels in peripheral lymphocytes in patients with schizophrenia correlate with severity of illness
Bibliographic record
Abstract
Schizophrenia is a disease that affects many areas of the brain. The dopamine hypothesis is one of the most widely-accepted ideas in the pathophysiology of schizophrenia. Besides alterations in the dopaminergic system in the central nervous system, there have been several reports of changes in dopaminergic systems in the peripheral blood of schizophrenic patients. Several reports have shown that dopamine receptor expression by lymphocytes is altered in patients with schizophrenia, but the results have been conflicting. We therefore re-assessed D3R and D4R mRNA levels in 11 patients with schizophrenia and 12 healthy subjects and correlated levels with severity of symptoms. D3R and D4R expression in lymphocytes and granulocytes was measured by quantitative RT-PCR and the severity of symptoms and cognitive impairment were assessed using the PANSS and BACS-J. There were no significant differences in mean D3R or D4R mRNA levels in lymphocytes from schizophrenic patients and controls and no significant difference in mean D4R mRNA levels in granulocytes (D3R mRNA undetectable). In patients with schizophrenia, D3R expression was inversely correlated with the total PANSS score (r = 0.768, p = 0.009), while D4R expression was positively correlated with working memory scales (r = 0.895, p = 0.001). In conclusion, these results imply that lymphocyte D3R and D4R are involved in the mechanisms of the disorder and could be used as target markers in the treatment of schizophrenia.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".