S169. MICROGLIAL ACTIVATION AND MORPHOLOGICAL BRAIN ALTERATIONS IN PSYCHOSIS AND PSYCHOSIS RISK
Bibliographic record
Abstract
Abnormal brain structural alterations and microglial activation are implicated in the pathophysiology of psychosis. However, the connection between these two pathologies is not yet well understood. Although previous studies suggested a link between the level of proinflammatory cytokines and abnormalities in brain structure in patients with schizophrenia, there is no in-vivo study investigating whether microglial activation is also linked to morphological brain alterations previously reported in individuals with psychosis and psychosis risk. In order to address the current gap in the literature, we investigated microglial activation and structural brain abnormalities in key brain regions affected in psychosis (i.e. hippocampus and dorsolateral prefrontal cortex) of a large group of participants (N = 90) including 35 individuals at clinical high risk (CHR) for psychosis, 27 first-episode psychosis (mostly antipsychotic naïve) patients, and 28 healthy volunteers. All the participants underwent a [18F]FEPPA positron emission tomography (PET) targeting mitochondrial 18 kDa translocator protein (TSPO) to determine microglial activation and a T1 MRI scan to study structural brain characteristics including brain volume, cortical thickness, and hippocampal shape. Using a vertex-wise analysis, we observed a significant microglial activation-by-diagnostic group interaction in morphological measures across the left hippocampus. We observed associations between microglial activation and outward and inward morphological alterations in the dorsal and ventro-medial portions of the left hippocampus, respectively. These associations were only observed in first-episode psychosis group. There was no association between [18F]FEPPA binding and other structural brain characteristics. Our results, for the first time, suggest a connection between microglial activation and morphological alterations in hippocampus of first-episode psychosis.
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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 | 0.000 | 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) | 0.016 | 0.001 |
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".