Comparative psychopharmacology of autism and psychotic-affective disorders suggests new targets for treatment
Bibliographic record
Abstract
The first treatments showing effectiveness for some psychiatric disorders, such as lithium for bipolar disorder and chlorpromazine for schizophrenia, were discovered by accident. Currently, psychiatric drug design is seen as a scientific enterprise, limited though it remains by the complexity of brain development and function. Relatively few novel and effective drugs have, however, been developed for many years. The purpose of this article is to demonstrate how evolutionary biology can provide a useful framework for psychiatric drug development. The framework is based on a diametrical nature of autism, compared with psychotic-affective disorders (mainly schizophrenia, bipolar disorder and depression). This paradigm follows from two inferences: (i) risks and phenotypes of human psychiatric disorders derive from phenotypes that have evolved along the human lineage and (ii) biological variation is bidirectional (e.g. higher vs lower, faster vs slower, etc.), such that dysregulation of psychological traits varies in two opposite ways. In this context, the author review the evidence salient to the hypothesis that autism and psychotic-affective disorders represent diametrical disorders in terms of current, proposed and potential psychopharmacological treatments. Studies of brain-derived neurotrophic factor, the PI3K pathway, the NMDA receptor, kynurenic acid metabolism, agmatine metabolism, levels of the endocannabinoid anandamide, antidepressants, anticonvulsants, antipsychotics, and other treatments, demonstrate evidence of diametric effects in autism spectrum disorders and phenotypes compared with psychotic-affective disorders and phenotypes. These findings yield insights into treatment mechanisms and the development of new pharmacological therapies, as well as providing an explanation for the longstanding puzzle of antagonism between epilepsy and psychosis. Lay Summary: Consideration of autism and schizophrenia as caused by opposite alterations to brain development and function leads to novel suggestions for pharmacological treatments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".