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Synaptic Density in Early Stages of Psychosis and Clinical High Risk

2024· article· en· W4404319577 on OpenAlex
M. Belen Blasco, Kankana Nisha Aji, Christian Ramos-Jiménez, Ilana R. Leppert, Christine Tardif, J. Pinto Cohen, Pablo Rusjan, Romina Mizrahi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJAMA Psychiatry · 2024
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsMontreal Neurological Institute and HospitalDouglas Mental Health University InstituteMcGill UniversityDouglas College
Fundersnot available
KeywordsPsychosisCannabisMedicineAntipsychoticInternal medicineMagnetic resonance imagingSchizophrenia (object-oriented programming)PsychologyPsychiatry

Abstract

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Importance: Synaptic dysfunction is involved in schizophrenia pathophysiology. However, whether in vivo synaptic density is reduced in early stages of psychosis, including its high-risk states, remains unclear. Objective: To investigate whether synaptic density (synaptic vesicle glycoprotein 2A [SV2A] binding potential) is reduced in first-episode psychosis (FEP) and in clinical high risk (CHR) and investigate the effect of cannabis use on synaptic density and examine its relationship with psychotic symptoms and gray matter microstructure across groups. Design, Setting, and Participants: This cross-sectional study was performed in a tertiary care psychiatric hospital from July 2021 to October 2023. Participants were patients with antipsychotic-free or minimally exposed FEP or CHR and healthy controls with a clean urine drug screen (except cannabis). Main Outcomes and Measures: Synaptic density was quantified with dynamic 90-minute [18F]SynVesT-1 positron emission tomography (PET) scans across prioritized brain regions of interest (ROIs) delineated in individual magnetic resonance images (MRIs). Cannabis use was confirmed with urine drug screens. Gray matter microstructure was assessed using diffusion-weighted MRI to estimate neurite density. Results: A total of 49 participants were included, including 16 patients with FEP (mean [SD] age, 26.1 [4.6] years; 9 males and 7 females), 17 patients at CHR (mean [SD] age, 21.2 [3.5] years; 8 males and 9 females), and 16 healthy controls (mean [SD] age, 23.4 [3.6] years; 7 males and 9 females). Synaptic density was significantly different between groups (F2,273 = 4.02, P = .02, Cohen F = 0.17; ROI: F5,273 = 360.18, P < .01, Cohen F = 2.55) with a group × ROI interaction (F10,273 = 2.67, P < .01, Cohen F = 0.32). Synaptic density was lower in cannabis users (F1,272 = 5.31, P = .02, Cohen F = 0.14). Lower synaptic density across groups was associated with more negative symptoms (Positive and Negative Syndrome Scale negative scores: F1,81 = 4.31, P = .04, Cohen F = 0.23; Scale of Psychosis-Risk Symptoms negative scores: F1,90 = 4.12, P = .04, Cohen F = 0.21). SV2A binding potential was significantly associated with neurite density index (F1,138 = 6.76, P = .01, Cohen F = 0.22). Conclusions and Relevance: This study found that synaptic density reductions were present during the early stages of psychosis and its risk states and associated with negative symptoms. The implications of SV2A for negative symptoms in psychosis and CHR warrant further investigation. Future studies should investigate the impact of cannabis use on synaptic density in CHR longitudinally.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.076
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.334
Teacher spread0.320 · 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