Multilevel Profiles of Neurobiological Profiles of Risk, and Resilience and Treatment Outcomes in Early-Stage Psychiatric Disorders: Associations With Longitudinal Functioning Trajectories-A Multi-Level Machine Learning Analysis
Bibliographic record
Abstract
Aims:The association between cannabis use and psychosis has emerged as a prominent societal and health service issue over the past decade.In this symposium, we provide a broad overview of the current state of the research into the prevalence and trends in cannabis related psychosis and also deal with potential mechanisms and new treatment approaches. Methods and Results:The first presentation provides an overview of the increasing prevalence of cannabis psychosis internationally and highlights that this is an issue of global concern.The second presentation explores the association between legalizing cannabis use and rates of adolescent psychosis in Canada.The third presentation presents data about the relationship between inflammatory markers and cannabis use in youth.The final presentation gives an overview of a new treatment clinic for people with psychosis and cannabis use disorder and gives the first outcome data from this innovative service.Our symposium will end with a discussant who has lived experience of a cannabis induced psychosis who will give his views of the research and thoughts on the future of this field.Conclusions: Taken together, these presentations provide an overview of trends and risk factors for cannabis psychosis alongside opportunities for intervention and support.Implications for policy and practice are discussed in partnership with an expert by experience. Paper: The Rise and Rise of Drug-Induced Psychosis Across the Globe (18085)1.05 Epidemiology, 2.07 Psychosis NOS Robin Murray, Institute of Psychiatry, Psychology and Neuroscience, Kings College London respondents aged 12-24 years at baseline with no prior psychotic disorder (N = 11,363).The primary outcome was days to first hospitalization, ED visit, or outpatient visit related to a psychotic disorder according to validated diagnostic codes.Due to non-proportional hazards, we estimated age-specific hazard ratios during adolescence (12-19 years) and young adulthood (20-33 years).Sensitivity analyses explored alternative model conditions including restricting the outcome to hospitalizations and ED visits to increase specificity.Results: Compared to no cannabis use, cannabis use was significantly associated with psychotic disorders during adolescence (aHR = 11.2;95% CI: 4.6-27.3),but not during young adulthood (aHR = 1.3; 95% CI: 0.6-2.6).When we restricted the outcome to hospitalizations and ED visits only, the strength of association increased markedly during adolescence (aHR = 26.7;95% CI: 7.7-92.8)but did not change meaningfully during young adulthood (aHR = 1.8; 95% CI: 0.6-5.4). Conclusions:This study provides new evidence of a strong but age-dependent association between cannabis use and risk of psychotic disorder, consistent with the neurodevelopmental theory that adolescence is a vulnerable time to use cannabis.The strength of association during adolescence was notably greater than previous studies, possibly reflecting the recent rise in cannabis potency. Paper: Cannabis Use in Youth is Associated With Chronic Inflammation (18088) 1.05 Epidemiology, 2.07 Psychosis NOS Emmet Power, RCSI University of Medicine and Health SciencesMarkers of inflammation and cannabis exposure are associated with increased risk of mental disorders.In the current study, we investigated associations between cannabis use and biomarkers of inflammation.Utilizing a sample of 914 participants from the Avon Longitudinal Study of Parents and Children, we investigated whether interleukin-6 (IL-6), tumour necrosis factor α (TNFα), C-reactive protein (CRP) and soluble urokinase plasminogen activator receptor (suPAR) measured at age 24 were associated with past year daily cannabis use, less frequent cannabis use and no past year cannabis use.We adjusted for a number of covariates including sociodemographic measures, body mass index, childhood trauma and tobacco smoking.We found evidence of a strong association between daily or near daily cannabis use and suPAR.We did not find any associations between less frequent cannabis use and suPAR.We did not find evidence of an association between IL-6, TNFα or CRP and cannabis use.Our finding that frequent cannabis use is strongly associated with suPAR, a biomarker of systemic chronic inflammation implicated in neurodevelopmental and neurodegenerative processes is novel.These findings may provide valuable insights into biological mechanisms by which cannabis affects the brain and impacts on risk of serious mental 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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".