October 10, 2022
Posted by:
IEPA
By Barnaby Nelson
Professor Barnaby Nelson, Head of the Ultra High Risk for Psychosis Research Program at Orygen and the Centre for Youth Mental Health, The University of Melbourne in Australia discusses the value of risk prediction for the field of mental health and the latest developments in research.
Some young people coming into mental health services may be experiencing a passing episode of symptoms, perhaps in reaction to stresses going on in their lives or the challenges of transitioning to adulthood. Others may have mild to moderate symptoms that persist at that level, maybe coming in and out of episodes over time. Other young people are in the early stages of prolonged, life-threatening and disabling serious mental disorder. All of these young people should receive clinical care. However, which track is an individual on? It would be very valuable to know this early on – that is, to be able to predict what the future might hold for an individual. We are currently unable to do this. Other fields of medicine – oncology (cancer), cardiovascular (heart) disease, cerebrovascular disease (stroke) – have risk calculators that can be used for individual patients. This is currently lacking in mental health.
There are several advantages of being able to forecast health and clinical outcomes. These include:
1. Promoting early intervention by directing our existing treatments to the highest risk subgroup.
2. Providing a window into the biological (e.g. brain changes), psychological (e.g. thinking styles) and social factors (e.g. discrimination) that contribute to risk and protection.
3. Helping us develop new treatments that specifically target these risk and protective factors.
The area of psychosis risk prediction that has received the most attention to date and has recently received another shot in the arm through a NIMH-funded global consortium, is the Accelerating Medicines Partnership (AMP®) – Schizophrenia, The Accelerating Medicines Partnership (AMP®) program is a public-private partnership between the National Institutes of Health (NIH), the U.S. Food and Drug Administration (FDA), the European Medicines Agency (EMA), pharmaceutical and life science companies, non-profits and other organizations. The overarching aim of the AMP program is to improve our understanding of illness pathways and identify new and better targets for treatment. The AMP Schizophrenia program was launched in 2020 to address the critical need for more effective treatments for people with schizophrenia and other psychoses. The aims of this global effort include developing tools that identify the early stages of psychosis risk and predicting the likelihood of progression to psychosis and other outcomes. A related aim is to help researchers identify new targets for drug-based treatments that can be tested in clinical trials.
The AMP Schizophrenia prediction tools will be developed based on a wide range of data types – clinical, neurocognitive, neurophysiological, neuroimaging, genetics, fluid biomarkers, speech and facial expression, and digital assessments. Some of these types of data may be useful for predicting outcomes when young people first come into clinics, whereas others may pick up on changes over time that may be ‘early warning signs’ of deterioration. For example, digital data collected via phones and wrist watches (daily surveys and diaries, activity patterns, sleep) are very fine grained and may identify subtle changes that signal imminent deterioration in mental state.
Apart from ‘sharpening the tools’ for predicting psychosis and developing new preventive treatments, the field is also ‘broadening the lens’ to identify risk for a broad range of severe mental disorders (severe depression, bipolar disorder, personality disorder, etc.), not just psychosis. This is particularly appropriate in young people in the early stages of disorder, where the range of symptoms is often diffuse and can evolve in a range of different directions. The field has suffered from researchers being too focused on a particular disorder of interest, which has blinkered us from recognising that many risk factors and mechanisms are in fact present across disorders. This means that early treatments targeting these risk factors and mechanisms may be useful in ‘killing multiple birds with one stone’.
On a final note, while much energy is justifiably spent on matching existing treatments to individual patients, newtreatment options are urgently required for psychotic and other disorders. There is an unacceptably high non-response rate to existing treatments and therefore some ‘outside the box’ treatment options need to be tested. One example of this currently being trialled at Orygen, a youth mental health research centre in Melbourne, is Hybrid, which combines advances in technology (Virtual Reality-based exposure therapy) and neuroscience (EEG-based neurofeedback) with established psychological therapy (CBT for psychosis) for auditory verbal hallucinations (‘hearing voices’). The aim is to show a person their brain activity in response to different situations presented via Virtual Reality (some of which trigger symptoms) and deliver psychological therapy at the same time. By doing this, a person may be able to gain greater control over their brain activity, particularly the activity associated with hearing voices, which may lead to a reduction in symptoms.
By developing these risk calculators, broadening the scope beyond single disorders, and developing a new arsenal of treatments, the effectiveness of early intervention for mental disorders can be maximised.
By developing these risk calculators, broadening the scope beyond single disorders, and developing a new arsenal of treatments, the effectiveness of early intervention for mental disorders can be maximised.
Professor Barnaby Nelson is Head of the Ultra High Risk for Psychosis Research Program at Orygen and the Centre for Youth Mental Health, The University of Melbourne. He is a practicing clinical psychologist with a particular interest in schizophrenia spectrum disorders. His research focuses on early identification strategies, prediction of outcome in high-risk youth, transdiagnostic aetiological mechanisms, integrating phenomenology with neuroscience, and preventive treatments, particularly psychotherapies and neurofeedback. Professor Nelson is Principal Investigator on the Prediction Scientific Global Consortium (PRESCIENT), one of the Research Networks involved in the Accelerating Medicines Partnership-Schizophrenia (AMPâ-SCZ) program
Barnaby will be a plenary speaker at our upcoming IEPA14 International Conference on Early Intervention in Mental Health, from July 10th-12th 2023 in Lausanne, Switzerland. Join us to find out more about the latest research and practice in this area. Further details are available here
References
Gandara, V., Pineda, J.A., Shu, I.W., Singh, F., 2020. A Systematic Review of the Potential Use of Neurofeedback in Patients With Schizophrenia. Schizophr Bull Open 1(1), sgaa005.
Gordon, J. A. & Heinssen, R. K. Collaborative Approaches to the Clinical High Risk State: From Data to Mechanism to Intervention. Biol Psychiat 88, 287–288 (2020).
Barron, D. (2019). Psychiatry Is Still Stuck in Freud’s Era. Big Data Can Revolutionize How We Care for Patients: https://time.com/6076797/big-data-psychiatry/
Hazell, C.M., Hayward, M., Cavanagh, K., Strauss, C., 2016. A systematic review and meta-analysis of low intensity CBT for psychosis. Clinical psychology review 45, 183-192.
McGorry, P.D., Hartmann, J., Spooner, R., & Nelson, B. (2018). Beyond the at risk mental state concept: Transitioning to transdiagnostic psychiatry. World Psychiatry, 17 (2), 133-142.
McGorry, P.D. & Nelson, B. (2016). Why We Need a Transdiagnostic Staging Approach to Emerging Psychopathology, Early Diagnosis and Treatment. JAMA Psychiatry, 73 (3), 191-192.
Nelson, B., Torregrossa, L., Thompson, A., Sass, L.A., Park, S., Hartmann, J.A., McGorry, P.D., Alvarez-Jimenez, M. (2021). Improving treatments for psychotic disorders: Beyond cognitive behavior therapy for psychosis. Psychosis, 13 (1), 78-84.
Declaration of Interests: None
Acknowledgements:
This project was made possible thanks to a sponsorship from H/Lundbeck A/S. The opinions expressed in these materials do not necessarily reflect those of H.Lundbeck.
