Antipsychotic Drug-Induced Increases in Peripheral Catecholamines are Associated With Glucose Intolerance
Bibliographic record
Abstract
The second-generation antipsychotic drugs are widely used in the field of psychiatry, for an expanding number of different conditions. While their clinical efficacy remains indispensable, many of the drugs can cause severe metabolic side-effects, resulting in an increased risk of developing cardiometabolic disorders. The physiological basis of these side-effects remains an ongoing area of investigation. In the present study, we examined the potential role of peripheral catecholamines in antipsychotic-induced glucose intolerance. Adult female rats were acutely treated with either the first-generation antipsychotic drug haloperidol (0.1, 0.5 or 1 mg/kg) or the second-generation drugs risperidone (0.25, 1.0 or 2.5 mg/kg), olanzapine (1.5, 7.5 or 15 mg/kg) or clozapine (2, 10 or 20 mg/kg) or vehicle. Fasting glucose levels were measured and then animals were subjected to the intraperitoneal glucose tolerance test. Levels of peripheral norepinephrine, epinephrine and dopamine were concurrently measured in the same animals 75, 105 and 135 min after drug treatment. All antipsychotics caused glucose intolerance, with strongest effects by clozapine > olanzapine > risperidone > haloperidol. Plasma catecholamines were also increased by drug treatment, with greatest effects for norepinephrine and epinephrine caused by clozapine > risperidone > olanzapine > haloperidol. Importantly, there were strong and statistically significant associations between norepinephrine/epinephrine levels and glucose intolerance for all drugs. These findings confirm that increases in peripheral catecholamines co-occur in animals that exhibit antipsychotic-induced glucose intolerance, and these effects are strongly associated with each other, providing further evidence for elevated catecholamines as a substrate for antipsychotic metabolic side-effects.
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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 | 0.000 | 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 | 0.001 |
| 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".