Meta-FENO
Research type
Research Study
Full title
Metacognitive Processes that Predict Outcome in First episode Psychosis – First Episode Psychosis Neuroimaging Observatory
IRAS ID
314697
Contact name
Rajeev Krishnadas
Contact email
Sponsor organisation
NHS Greater Glasgow and Clyde
Duration of Study in the UK
1 years, 4 months, 30 days
Research summary
Psychosis is an illness manifest by unusual or muddled thoughts and hearing voices. Psychosis is the fifth leading UK cause of disability among working age adults. At a group level, we know factors like duration of untreated psychosis are associated with worse outcomes. However, we struggle to predict who will do well at an individual level.
Prediction modelling is an advanced statistical technique which has the potential to revolutionise medicine by the prediction of outcomes at an individual level. Existing prediction models in First Episode Psychosis (FEP) focus on using only routine clinical and demographic data. We believe that additional information about the underlying disease processes in FEP may improve the performance of prediction models. For example, people with psychosis can have increased levels of inflammation in the blood and also abnormalities in levels of glutamate in the brain, a chemical which helps nerve cells communicate. In addition, there is evidence for abnormalities in the connections between nerve cells in the brain.
In this project, we are using advanced computational techniques on behavioural and EEG/ fMRI data to extract variables that cannot be measured directly (also known as latent variables). We believe that these variables will help in better predicting outcomes in FEP, when combined with routinely collected data (including questionnaires) and glutamate (measured using MRS) and other levels of inflammation (from blood samples).
REC name
West of Scotland REC 4
REC reference
23/WS/0004
Date of REC Opinion
7 Feb 2023
REC opinion
Further Information Favourable Opinion