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Record W4407419484 · doi:10.1093/ijnp/pyae059.408

MICROGLIAL ACTIVATION IN MEDICATED PATIENTS WITH FIRST-EPISODE PSYCHOSIS: PRELIMINARY RESULTS FROM A [18F]DPA-714 PET IMAGING STUDY

2025· article· en· W4407419484 on OpenAlexaboutno aff
Yuya Mizuno, Tiago Reis Marques, Julia Schubert, Mattia Veronese, Federico Turkheimer, Oliver Howes

Bibliographic record

VenueThe International Journal of Neuropsychopharmacology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosisPet imagingNeurosciencePsychologyMedicinePsychiatryPositron emission tomography

Abstract

fetched live from OpenAlex

Abstract Background Dysfunction of brain-resident microglia is hypothesised to play a key role in the development of mental disorders including schizophrenia (1). The 18-kDa translocator protein (TSPO) is known to be a sensitive and robust biomarker of microglial activation in the brain (2). Using PET imaging, previous studies, including from our group (3), have shown increased expression of TSPO in the brains of patients with schizophrenia relative to controls (4). However, findings across studies have been inconsistent, with others indicating no change or decreased TSPO expression in patients (5). Thus, it remains unclear if microglial activation plays a primary role in the illness. Aims & Objectives To test the relevance of microglial activation in schizophrenia, we carried out a randomised, placebo-controlled study involving 3-month intervention with natalizumab in patients with first-episode psychosis, combined with longitudinal assessments of central/peripheral immune markers (ClinicalTrials.gov NCT03093064). Here, we present findings from the baseline case-control comparison of the study. Methods Case-control comparison of patients with first-episode psychosis and matched healthy controls. Patients were recruited from community Early Intervention services across London. Healthy controls, with no history of psychosis and matched for age, sex, and TSPO genotype, were recruited from the same geographical area. As a marker of microglial activation, we used [18F]DPA-714 PET imaging and quantified TSPO binding using the supervised clustering algorithm (6). Total, temporal, and frontal gray matter (GM) were defined as a priori regions of interest (ROI). Serum and cerebrospinal fluid (CSF) samples were collected for cytokine analysis. Symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS), Scale for the Assessment of Negative Symptoms (SANS), and Calgary Depression Scale for Schizophenia (CDSS). Results 62 patients with DSM-5 psychotic disorders (mean age 27.5, 42 male, median duration of illness 22 months) and 41 healthy controls (mean age 29.2, 23 male) completed baseline assessments. Groups did not differ significantly in demographic variables including age, sex, ethnicity, and BMI. All patients were on antipsychotic treatment with a median chlorpromazine equivalent dose (7) of 287mg/day. ANCOVA with age and TSPO genotype included as covariates showed that TSPO binding was elevated in patients compared to controls in the total GM (mean± SE 1.098±0.002 vs. 1.091±0.003, p=0.038, partial eta squared 0.043) and temporal GM (mean± SE 1.095±0.003 vs. 1.084±0.004, p=0.016, partial eta squared 0.057). There was no significant difference in TSPO binding in the frontal lobe GM. Serum and CSF cytokine analyses are ongoing. There was no significant correlation between PANSS total or subscale scores, SANS negative symptom scores, or CDSS depressive symptom scores and TSPO binding in the a priori ROIs. Discussion & Conclusions Baseline case-control comparison from this study indicates that microglial activation is increased in the total and temporal lobe GM of patients with first-episode psychosis relative to controls. This is the largest investigation to date quantifying microglia activation in patients with psychotic disorders. Implications of the PET findings will be discussed in the context of ongoing investigations of serum/CSF cytokines. References 1.Calcia et al., Psychopharmacology (Berl), 2016 2.Turkheimer et al., Biochem Soc Trans, 2015 3.Bloomfield et al., Am J Psychiatry, 2016 4.Reis Marques et al., Psychol Med, 2019 5.Plavé n-Sigray et al., Biol Psychiatry, 2018 6.Schubert et al., Eur J Nucl Med Mol Imaging, 2021 7.Leucht et al., Schizophr Bull 2016

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.014
GPT teacher head0.299
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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