Investigation of the Effects of Antipsychotics on CNS Insulin-mediated Brain Glucose Uptake using 2DG Autoradiography
Bibliographic record
Abstract
Antipsychotics (APs) drugs are associated with adverse metabolic side effect. Recent studies have shifted focus onto the central nervous system (CNS) suggesting that APs can induce central insulin resistance and disrupt glucose regulation. Attenuated central insulin action has also been shown to be a critical factor in the development of age-related cognitive decline and Alzheimer’s disease (AD). As such, aberrant brain insulin signaling has been posited to lie at the crossroads of metabolic and cognitive disorders. In recent years, a greater focus has been placed on using insulin delivered to the brain as a potential treatment intervention. Thus, we conducted a systematic review and meta-analysis to examine the cognitive outcomes and clinical implications of patients and healthy individuals treated with intranasal insulin. We discovered that intranasal insulin failed to improve cognition in AP-treated chronic patients with schizophrenia in comparison to the pro-cognitive benefits observed for patients with AD/mild cognitive impairment. Next, we sought to determine if APs impaired central insulin action by measuring insulin-mediated cerebral glucose uptake using 2-Deoxy-D-glucose autoradiography. We discovered that olanzapine attenuated central insulin-mediated cerebral glucose uptake across various regions of the brain. We also investigated whether this was a class or dopamine 2 receptor (D2R) antagonism driven effect by using four additional APs (haloperidol, raclopride, risperidone, and aripiprazole) with varying receptor affinities. We determined that all APs, regardless of class, also induced central insulin resistance in regions responsible for reward processing, motivation, metabolism, as well as cognition. Taken together, our findings suggest that an acute dose of AP can induce brain insulin resistance in a rodent model which may explain the lack of efficacy of intranasal insulin for patients taking APs due to pre-existing insulin resistance in the brain.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".