bioRxivNeuroscience
Causal Discovery Analysis Reveals Insights into Psychosis Proneness, Brain Function, and Environmental Factors among Young Individuals
Tuba Sahin-IlikogluiD, Sisi MaiD, Erich KummerfeldiD, Eric RawlsiD, Hao Yang TaniD, Timothea ToulopoulouiD
Abstract
BackgroundExperiencing symptoms of psychosis, such as delusions and hallucinations, are observed in general, nonclinical populations. These experiences are sometimes described as psychosis proneness (PP) and potentially part of the psychosis continuum. The directional relationships among various factors contributing to psychosis proneness and its interactions, encompassing both environmental and neural mechanisms, lack comprehensive description. We aimed to identify targets to prevent psychosis proneness and its interactions by characterizing pathways using causal discovery analysis (CDA). MethodsParticipants were 194 healthy adolescent and young adult twin and sibling pairs aged between 14-24 years from Turkiye. They completed comprehensive assessments evaluating sociodemographic status, environmental risk, general intelligence, self-schema, PP, and working memory (WM) performance during fMRI (37 variables). CDA was applied, a novel machine learning algorithm, to understand the causal relationships of PP. ResultsThe analysis identified negative self-schema as having the largest causal effect among all assessments in PP [Effect size (ES)= 0.55]. Secondly, social cohesion and trust (SC&T) had a protective causal effect on PP [ES= -0.18]. Lastly, PP was identified as a direct cause of greater activation in DLPFC (BA9a-BA46v) during manipulation in the WM (ES= 0.14). ConclusionsCDA provides directionality of the 37 variables which were not presented earlier. The findings highlight the significance of negative self-schema and SC&T in the general population with PP, emphasizing the potential for preventive interventions targeting these factors. These findings also suggest a role for DLPFC as a potential target in this regard. To our knowledge, this is the first study using data-driven analysis to model causal mechanisms in PP in the general population.
- Citations
- 3
- FWCI
- 0.88
- Field percentile
- top 24%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Brain Functional Connectome Defines a Transdiagnostic Dimension Shared by Cognitive Dysfunction and Psychopathology in Preadolescents
Xiang Xiao, Christopher Joseph Hammond, … Yihong Yang·bioRxiv·Oct 14, 2021
- Neural correlates of reward anticipation in 2000 children aged 9-10 years: relation to psychotic-like experiences and depressive symptoms
Lisa Ronan, Graham K. Murray·bioRxiv·Sep 19, 2018
- Individual-Level Associations of Cognition and Personality With Adolescent Mental Health Vary Across Brain and Environmental Profiles
Jiadong Yan, Bin Wan, … Sherif Karama·bioRxiv·Jun 19, 2026
- A generic decision-making ability predicts psychopathology in adolescents and young adults and is reflected in distinct brain connectivity patterns
Michael Moutoussis, Benjamín Garzón, … Raymond J. Dolan·bioRxiv·Aug 20, 2020
- Dopamine D1 receptor availability is not associated with delusional ideation measures of psychosis proneness
Granville James Matheson, Pontus Plavén‐Sigray, … Simon Červenka·Schizophrenia ResearchPeer-reviewed·Jun 29, 2020
- Disruptions in White Matter Maturation and Mediation of Cognitive Development in Youth on the Psychosis Spectrum
Catherine E. Hegarty, Dietsje Jolles, … Katherine H. Karlsgodt·Biological Psychiatry Cognitive Neuroscience and NeuroimagingPeer-reviewed·Dec 27, 2018