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Record W4402703778 · doi:10.1101/2024.09.12.612734

Converging effects of cannabis and psychosis on the dopamine system: A longitudinal neuromelanin-sensitive MRI study in cannabis use disorder and first episode schizophrenia

2024· preprint· en· W4402703778 on OpenAlexaffabout
Jessica Ahrens, Sabrina D. Ford, Betsy Schaefer, David Reese, Ali R. Khan, Philip G. Tibbo, Rachel A. Rabin, Clifford Cassidy, Lena Palaniyappan

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsDalhousie UniversityWestern UniversityLawson Health Research InstituteMcGill UniversityDouglas College
Fundersnot available
KeywordsNeuromelaninPsychosisCannabisPsychologyPsychiatrySchizophrenia (object-oriented programming)DopamineMedicineClinical psychologySubstantia nigraNeuroscienceDopaminergic

Abstract

fetched live from OpenAlex

Abstract Importance Despite evidence that individuals who use cannabis early in life are at elevated risk of psychosis and that the neurotransmitter dopamine has a role in both conditions, the mechanism linking the two conditions remains unclear. Objective To use neuromelanin-sensitive MRI (neuromelanin-MRI), a practical, proxy measure of dopamine function, to assess whether a common alteration in the dopamine system may be implicated in cannabis use and psychosis and whether this alteration can be observed in cannabis users whether or not they have a diagnosis of first-episode schizophrenia. Design, Setting, and Participants This longitudinal observational study recruited participants from 2019 to 2023 from an early intervention service for psychosis in London, Ontario, Canada. The sample consisted of 25 participants with cannabis use disorder (CUD) and 36 participants without CUD (nCUD), of which 28 had first-episode schizophrenia (FES). One-year follow-up was completed for 12 CUD and 25 nCUD participants. Main Outcomes and Measures Neuromelanin-MRI contrast within the substantia nigra (SN) and within a subregion previously linked to psychosis severity (a priori psychosis region of interest) and diagnoses of schizophrenia-spectrum disorder and cannabis use disorder derived from the Structured Clinical Interview for DSM-5. Linear mixed effects analyses were performed relating neuromelanin-MRI contrast to clinical measures. Results We found that CUD was associated with elevated neuromelanin-MRI signal in a cluster of ventral SN voxels (387 of 2060 SN voxels, p corrected =0.027, permutation test). Furthermore, CUD was associated with elevated neuromelanin-MRI signal in an SN subregion previously documented to have elevated signal in relation to untreated psychotic symptoms (t 92 =2.12, p=0.037). In contrast, FES was not associated with a significant alteration in neuromelanin-MRI signal (241 SN voxels had elevated signal, p corrected =0.094). Conclusions and Relevance These findings suggest that elevated dopamine function in a critical SN subregion may contribute to the risk of psychosis in people with CUD. Thus, cannabis affects the long-suspected ‘final common pathway’ for the clinical expression of psychotic symptoms. Imaging the dopamine system with neuromelanin-MRI may index long-term dopamine turnover. Key Points Question Is the same midbrain dopamine pathway impacted by cannabis as in psychosis? Findings Cannabis use disorder participants had elevated neuromelanin-MRI signal in a cluster of ventral substantia nigra voxels and in a subregion previously documented to have elevated signal in relation to untreated psychotic symptoms. Meaning Increased dopamine functioning in the ventral substantia nigra may contribute to the risk of psychosis in people with cannabis use disorders.

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)0.003
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 score0.088
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.241
Teacher spread0.230 · 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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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