Investigating who are at most at harm from cannabis use and identifying actionable predictors of risk of transition to psychosis

Lead Supervisor
Professor Sagnik Bhattacharyya
Professor of Translational Neuroscience & PsychiatryDepartment of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London
sagnik.2.bhattacharyya@kcl.ac.uk 

Co-supervisor
Dr Ben Carter
Biostatistics & Health Informatics Department, King’s College London

Project Details

Adolescence is a period of heightened risk for the emergence of a number of mental disorders, in particular psychosis. Childhood through to adolescence is also a period when the growing brain is particularly vulnerable to the harmful effects of various risk factors for mental disorders, in particular, psychoactive drugs such as cannabis, which is arguably one of the most preventable risk factors for development of psychosis. While a large body of evidence to date has demonstrated the association of cannabis use and the risk of onset of psychosis, this has not led to identification of actionable predictors of those most at risk nor identification of determinants of risk at the individual level. The present proposal aims to address this by employing an enrichment sampling strategy to help identify young people most at harm from cannabis use, so as to enable risk stratification and targeted intervention. For this purpose, the present study will benefit from access to a large cohort (n~500) of young people presenting with a clinical high-risk state for psychosis (CHR) being recruited for existing funded studies, for whom baseline and multi-point follow-up data will be available.

The student will be involved in conducting follow up of this cohort as part of a team of researchers and employ a range of statistical approaches for analysis of longitudinal panel data (such as multivariate survival analyses, fixed-effects analyses, cross-lagged modelling etc) to investigate the effects of cannabis use on risk of transition to psychosis after accounting for the effects of time-invariant (e.g. genetic and pre-morbid environmental exposure) and time-varying (eg other drugs, pre-existing symptoms of psychosis) factors and identify predictors and determinants of risk. Identified predictors will then be used to develop an individualized multi-factorial risk prediction tool to detect sensitivity to harm from cannabis in CHR people. While CHR people have a very high risk of transition to frank psychosis, particularly those who use cannabis, not everyone develops a psychotic disorder. Furthermore, it is not possible to predict at an individual level who might develop a psychotic disorder. Therefore, the proposed tool will be an important first step towards identifying which of these young people are most at risk of developing psychosis so as to offer personalized intervention to those that are most at risk.  

Research training: Formal Supervision- Throughout the studentship, the student will receive structured as well as unstructured supervision and informal training from the primary supervisor (Prof Sagnik Bhattacharyya) and 2nd supervisor (Dr Ben Carter) through individual as well as individual supervision sessions. A bespoke training programme will be drawn early on in the PhD in consultation with the student.

The student will receive hands-on training in the conduct of research interviews as well as in the use of the specific psychiatric rating scales for use in the study.

Datasets

For this purpose, the present study will benefit from access to a large cohort (n~500) of young people presenting with a clinical high-risk state for psychosis (CHR) being recruited for existing funded studies, for whom baseline and multi-point follow-up data will be available. 

Keywords

Cannabis, clinical high-risk for psychosis, transition, risk prediction