Traditional psychiatry based on symptoms-based disorder categories is limited by poor understanding of the underlying causes and mechanisms of psychiatric disorders, the appearance of the same symptoms in many psychiatric disorders and poor treatment outcomes. A new approach based on the assumption that mental illnesses are disorders of brain circuits — the Research Domain Criteria (RDoC) — will enable better diagnosis and tailored interventions, explained Professor Marianne Goodman, New York, at ECNP 2021.
To achieve precision psychiatry and thereby improved outcomes for people with mental illness, it is essential to address the many limitations of traditional psychiatry, said Professor Goodman. These include:
- Limited understanding of the pathophysiology of psychiatric disorders1
- The overlap of symptoms across many psychiatric disorders2
- The inability to accurately match patients to treatments, which are often used in a trial-and-error manner
- The lack of diagnostic tools and technologies2
Increasing understanding of pathophysiology
Need for a framework beyond traditional disorder categories based on symptoms
The Research Domain Criteria (RDoC) project was launched by the National Institute of Mental Health in 2010 to create a framework for research on the pathophysiology and future classification of mental disorders based on the assumption that mental illnesses are disorders of brain circuits.3
The aim is to rethink research by building a framework beyond symptoms and traditional disorder categories based on symptoms, explained Professor Goodman.
A domain-based framework approach predicts clinical outcomes
RDoC takes into account four major factors:
- Neurodevelopment
- Environmental effects
- Domains — negative valence, positive valence, cognitive systems, systems for social processes, arousal/regulatory systems, and sensorimotor systems
- Units of analysis — genes, molecules, cells, circuits (neural systems and behavioral dimensions), physiology, behavior and self-reports4
RDoC domains have been shown to predict clinical outcomes in terms of duration of hospital stay and readmission risk — based on an analysis of electronic health records (EHR) for 2010 psychiatric patients,5 said Professor Goodman.
The importance of biomarkers
Biosignatures comprised of biomarkers can be applied to individuals and populations to produce tailored interventions
Biomarkers are being discovered through molecular science research, big data (e.g. using EHRs, mobile device data), cognitive neuroscience and analysis of individual characteristics and environmental factors, said Professor Goodman, and may form an important part of precision psychiatry.
Sets of biomarkers can be used to produce biosignatures, which can be applied to individuals and populations to produce better diagnosis, endophenotype, disease classifications, prognosis and tailored interventions.2
Psychiatric illness can be formulated as a dysfunction in transdiagnostic neurobehavioral phenotypes, such as neurocircuit activation
To illustrate this approach, Professor Goodman highlighted a neuroimaging meta-analysis of 298 studies involving 5427 patients with psychiatric disorders and 5491 controls, which demonstrated neurocircuit dysfunction among those with psychiatric disorders.6
The dysfunction affected areas key for emotional processing including the amygdala, hippocampal and parahippocampal gyri and prefrontal regions.6
The authors concluded that psychiatric illness may therefore be formulated as a dysfunction in transdiagnostic neurobehavioral phenotypes such as neurocircuit activation, which is consistent with RDoC.6
Support for this hypothesis is provided by the demonstration that impaired amygdala-based activity is related to different network dysfunctions in major depressive disorder,7 added Professor Goodman.
Educational financial support for this symposium was provided by Boehringer Ingelheim.
