Early Intervention and Prevention

The UK is a global leader in the delivery of national, evidence-based early intervention in psychosis. Our goal is to extend the breadth of this impact to common mental health disorders, such as depression, bipolar disorder and anxiety disorders. By intervening earlier in the life-course we are taking a truly preventative approach with focus on potential causes including bullying, deprivation, substance misuse and childhood trauma.

The development of early intervention services for psychosis across the UK has been a uniquely effective NHS innovation, led by pioneering service developments in Birmingham and Australia in the 1990’s; aiming to improve clinical outcomes, reduce the societal burden of psychosis and the healthcare costs. The UK has a universal healthcare system, and Birmingham the largest 0-25 mental health service in the UK. Our comprehensive clinical infrastructure has contact with thousands of young people with early psychosis and developing mental health disorders every year and therefore provides a unique opportunity for such impact.

Our current research:

Psychosis Immune Mechanism Stratified Medicine Study

Key people: Professor Rachel Upthegrove

In collaboration with the University of Cambridge, we have recently been awarded a major grant from the Medical Research Council to investigate the link between increased brain inflammation and psychosis. Evidence suggests that inflammation may be present before and during the early stages in some, but not all young people with psychosis. In this multicentre Psychosis Immune Mechanism Stratified Medicine Study, Professor Upthegrove and Dr Khandaker will lead a team of investigators, including University of Birmingham MDS Professors Nicholas Barnes, and George Gkoutos, to examine how immune dysfunction could cause psychosis and use advanced AI techniques to identify who might benefit most from novel immune targeted treatments.

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Midlands Engine: Mental Health Pilot

 Key people: Professor Steven Marwaha

Studies show that at any one time, a sixth of the population in England aged 16 to 64 has a mental health problem, which costs employers between £33 billion and £42 billion a year in lost productivity. Recognising the huge impact mental health issues have on employees’ wellbeing and employers’ productivity, the Midlands Engine Mental Health and Productivity Pilot has been created to break down the barriers to people suffering mental health problems and facilitate their return to work.

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Testing a model of altered memory processes in psychosis and autism-spectrum disorder

Key people: Dr Kareen Heinze

This study looks into the mechanisms and shared neurobiology of memory impairments in young people with a diagnosis or autism and/or psychosis.

Our PhD research:

Neuroimaging & Metabolic Biomarker Predictors of Recovery from Depression and Psychosis

Depression is the leading cause of disability world-wide with 300 million people being affected. Adolescents and young people are particularly vulnerable to developing this illness. In the UK, the one-year prevalence of depression in adolescents is 5%. While around 60% of young people with depression fully recover, a large proportion will have ongoing difficulties. Depression is also the most common co-morbidity seen with other mental disorders such as psychosis. Complex psychopathology presents clinicians with the challenge of correctly identifying co-morbidities, avoiding misdiagnoses, and tailoring therapeutic options for the individual. 

Currently, clinicians treat depression with co-morbid psychosis the same way they treat major depressive disorder on the presumption that they have the same neural basis. Data from the PRONIA study, an EUFP7 funded 8 centre study recruiting recent onset depression and recent onset psychosis participants will be used to identify common and distinct neuroimaging, clinical, and metabolic features of depression across diagnostic groups. Features that provide significant information will be used to build predictive machine learning models that predict recovery from depression with co-morbid psychosis as well as diagnostic machine learning models.

PhD student: Paris Lalousis

Supervisors: Professor Rachel UpthegroveProfessor Stephen WoodProfessor Nikolaos KoutsoulerisDr. Lianne SchmaalDr. Renate Reniers