200. Neuroinflammation in Individuals at Clinical High Risk for Psychosis: A PET Study With [(18)F]-FEPPA
Bibliographic record
Abstract
Background: A growing body of literature suggesting a prominent role of neuroinflammation in schizophrenia. Positron emission tomography (PET) imaging using ligands that bind to mitochondrial translocator protein 18 kDa (TSPO) is a unique way to study microglia activity as an in-vivo marker of neuroinflammation. Previous PET studies using TSPO radiotracer were limited by low affinity of radiotracer used, resolution of scanners used, small sample size, and the confounding effect of antipsychotic medications. There is a dearth of literature on neuroinflammation in individuals at clinical high risk for psychosis. Methods: Using a novel second-generation PET radiotracer for TSPO [(18)F]-FEPPA, we evaluated neuroinflammation in several brain regions relevant to schizophrenia (i.e. dorsolateral prefrontal cortex, hippocampus, medical prefrontal cortex, temporal cortex, total gray matter, and whole brain). Twenty five antipsychotic-naive individuals at clinical high risk for psychosis and 24 healthy volunteers underwent [(18)F]-FEPPA PET, using a high-resolution research tomograph (HRRT), and a structural (PD) MRI. PET data analyses were conducted using the validated 2-tissue compartment model with an arterial plasma input function to determine the total volume of distribution (VT) of [(18)F]-FEPPA. All subjects were categorized as high-, medium-, or low-affinity [(18)F]-FEPPA binders based on their rs6971 genotype, and imaging outcomes were adjusted based on these information. The Structured Interview for Psychosis-risk Syndromes was used to assess psychotic symptoms in the high-risk group, while the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was utilized to evaluate their cognitive function. Results: No significant group effects were found for [(18)F]-FEPPA binding across different ROIs after controlling the results for TSPO gene polymorphism. No significant correlations were observed between [(18)F]-FEPPA VTs and severity of psychotic symptoms and cognitive performance for any regions of interest (P > .05). Conclusion: Results of this study, do not suggest increased neuroinflammation in the brain of individuals at clinical high risk for psychosis as compared to matched healthy volunteers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".