1702-P: High Circulating MIF Levels Indicate the Association with Atypical Antipsychotic-Induced Metabolic Adverse Effects
Bibliographic record
Abstract
Atypical antipsychotics (AAPs) are first-line medications for schizophrenia (SZ). However, their use is frequently associated with the development of metabolic adverse effects, and the mechanisms behind these negative effects remain inadequately elucidated. Macrophage migration inhibitory factor (MIF) is a procytokine and involved in the development of metabolic dysfunction. To investigate the role of MIF in regulating antipsychotic-induced metabolic abnormalities, we recruited 142 healthy individuals and 388 SZ patients who had been receiving either typical antipsychotic (TAP) or AAP treatments. Subsequently, we conducted assessments of metabolic indices and measured plasma MIF levels, followed by a comprehensive statistical analysis to investigate the connection between MIF levels and metabolic dysfunction. A significant increase in plasma MIF levels was observed in groups receiving monotherapies with five major AAPs in comparison to healthy controls (all p < 0.0001). There was no such increase shown in the group receiving TAP treatment (p > 0.05). Elevated plasma MIF levels displayed a notable correlation with insulin resistance (β = 0.024, p = 0.020), as well as with the levels of triglycerides (β = 0.019, p = 0.001) and total cholesterol (β = 0.012, p = 0.038) in the groups receiving AAPs. However, while the TAP group also displayed some degree of metabolic dysfunction compared to healthy controls, no significant association was evident with plasma MIF levels (all p > 0.05). In conclusion, Plasma MIF levels exhibit a distinctive correlation with metabolic abnormalities triggered by AAPs. Thus, MIF could be further developed as a unique marker to monitor AAP-induced metabolic adverse effects in clinical settings. Disclosure X. Chen: None. P. Gao: None. Y. Qi: None. D. Cui: None. D. Qi: None. Funding This study was supported by National Sciences and Engineering Research Council of Canada (NSERC: RGPIN-2017-04542) and Canadian Institutes of Health Research (CIHR Project Grant: PJT-156116) for Dr. Qi.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| 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".