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Record W4407387037 · doi:10.1093/ijnp/pyae059.409

ASSOCIATIONS BETWEEN NEUROMELANIN ACCUMULATION IN PATIENTS WITH SCHIZOPHRENIA AND TREATMENT RESPONSIVENESS: A CROSS- SECTIONAL NM-MRI STUDY

2025· article· en· W4407387037 on OpenAlexaff
Fumihiko Ueno, Yusuke Iwata, Shiori Honda, Guillermo Horga, Clifford Cassidy, Edgardo Torres‐Carmona, Jianmeng Song, Vincenzo De Luca, Sakiko Tsugawa, Yoshihiro Noda, Mahavir Agarwal, Philip Gerretsen, Shinichiro Nakajima, Ariel Graff‐Guerrero

Bibliographic record

VenueThe International Journal of Neuropsychopharmacology · 2025
Typearticle
Languageen
FieldChemistry
TopicDye analysis and toxicity
Canadian institutionsRoyal Ottawa Mental Health CentreUniversity of OttawaUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsNeuromelaninSchizophrenia (object-oriented programming)Cross-sectional studyPsychologyPsychiatryMedicineNeuroscienceClinical psychologyPathologyDopamineSubstantia nigraDopaminergic

Abstract

fetched live from OpenAlex

Abstract Background Neuromelanin (NM) is a byproduct of monoamine metabolism, including that of dopamine. NM-sensitive Magnetic Resonance Imaging (NM-MRI) sequences enable the in vivo quantification of NM levels in the substantia nigra (SN). The NM-MRI signal is considered a surrogate marker for the integrity of SN dopamine neurons and, consequently, striatal dopaminergic functioning. Elevated striatal dopamine synthesis is associated with patients responsive to first-line antipsychotics (FLR) in schizophrenia, while normal striatal dopamine synthesis is implicated in the pathophysiology of treatment-resistant schizophrenia (TRS). Clozapine is the only antipsychotic currently approved for TRS. However, no studies have yet explored the relationship between SN accumulations, as measured by NM-MRI, and clozapine response in TRS patients. Aims & Objectives The study aims to investigate differences in dopaminergic activities among schizophrenia patients based on their treatment response, using NM-MRI. Methods The study enrolled TRS patients who either did not respond to clozapine (ultra-resistant schizophrenia [URS]) or did respond (non-URS), along with FLR patients and healthy controls (HCs). TRS was defined as resistance to at least two first-line antipsychotics and ongoing clozapine treatment at the time of the study. SN-NM levels were measured using 3T-MRI. The Contrast Ratio (CR) was calculated as the relative signal intensity difference between the SN and the crus cerebri. SN-CR values were compared between groups, controlling for age and sex. Associations between SN-CR and symptom severity scores were also explored within patient groups. Results A total of 78 participants (URS: n=16; non-URS: n=16; FLR: n=20; HCs: n=26) completed the study. Overall group differences in SN-CR values were significant (F(3,72)=3.80, η2=0.21, p=0.001). Specifically, URS patients (Cohen’ s d=0.86, p=0.049) and FLR patients (Cohen’ s d=1.27, p<0.0001) exhibited higher SN-CR values compared to HCs. No associations were found between SN-CR values and symptom severity scores within each group or the entire patient cohort. Discussion & Conclusion This study is the first to assess a proxy measure of mesostriatal dopamine function in schizophrenia patients, stratified by treatment responsiveness, using NM-MRI. We observed elevated SN-NM contrast in URS and FLR patients compared to HCs, and levels similar to HCs in non-URS patients. Longitudinal studies are warranted to determine whether SN-NM levels can serve as a reliable biomarker for predicting treatment response in schizophrenia.

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 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)0.000
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 score0.005
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.027
GPT teacher head0.363
Teacher spread0.337 · 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 teacher head, 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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Citations0
Published2025
Admission routes1
Has abstractyes

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