Skip to main content

The Prelude to Psychosis: Brain network analysis in emerging schizophrenia

Periodic Reporting for period 2 - PRE-PSYCH (The Prelude to Psychosis: Brain network analysis in emerging schizophrenia)

Reporting period: 2019-04-01 to 2020-03-31

Schizophrenia, in its most typical form, is characterized by recurrent episodes of psychosis interspersed with periods of (partial) remission. During a psychotic episode, people experience hallucinations, delusions, thought problems, and/or behavioral disturbances. The first episode of psychosis tends to manifest in adolescence or early adulthood and this is when schizophrenia is usually diagnosed. However, research has shown that changes in behavior and functioning precede the first psychotic episode. Early signs of impending psychosis include feelings of (mild) suspiciousness, social withdrawal, or a drop in school or job performance. These warning signs suggest that the underlying brain disturbance is already ongoing in the so-called prodromal phase, which is the period of imminent risk for psychosis. This project aimed to advance our understanding of what happens in the brain during this 'prelude to psychosis'.

This project is important for society because mental illness is among the leading cause of disability for adolescents and young adults. Mental disorders give rise to a broad cost to society through reduced adult productivity and increased healthcare costs. By clarifying what happens in the brain as psychosis first develops, this project aims to contribute to the development of early detection and intervention strategies for serious mental illness. Intervening early in emerging psychotic illness is important on a personal level because it may mitigate the effects of the illness for youth who are vulnerable to psychosis and on a societal level by curbing rising mental healthcare costs.

The conclusions of the action are that at-risk youth exhibit abnormalities in the brain's functional organization, and that abnormalities in the organization and connectivity of functional brain networks predict subsequent conversion to psychosis. Moreover, we were able to replicate our findings that brain network disturbances predate illness onset in an independent dataset of children with a familial risk for psychosis. In this dataset, functional brain network disturbances were associated with behavioral precursors of future psychopathology, including internalizing problems. These findings suggest that early interventions that target these networks may help avert the progression from early behavioral problems to mental illness in at-risk youth.
In this project, we used data from the Shanghai At Risk for Psychosis (SHARP) program. As part of this research program, a large sample of adolescents and young adults (mostly between 15 and 25 years of age) with early signs of impending psychosis was recruited at the Shanghai Mental Health Center. Clinical symptoms and cognitive functioning, as well as brain MRI data were collected and processed by labs at Harvard and MIT. For the current project, we used MRI data to reconstruct the brain network for each individual participant and analyzed these networks using graph theoretical analysis.

We mapped functional brain networks based on functional MRI data. We were specifically interested in the way that the functional connectome is organized into distinct communities. These communities or modules consist of sets of brain areas that are highly interconnected but have relatively poor connectivity with regions outside of their community. We found that youth with warning signs of impending psychosis, particularly those that go on to develop a psychotic episode, show abnormalities in the organization of these functional communities. Specifically, a number of brain regions that have been linked to (early-course) schizophrenia were found to change community affiliation. For example, superior temporal gyrus, which comprises the auditory cortex and has been implicated in auditory verbal hallucinations, changed affiliation from the sensorimotor to the limbic module. These findings are consistent with hypotheses that abnormal interactions between sensory and limbic systems may be involved in the development of psychotic symptoms. These findings were published in Molecular Psychiatry, a top-ranking journal in biological psychiatry and were picked up by several news outlets including SciTech Daily (https://scitechdaily.com/neuroscientists-identify-brain-activity-pattern-linked-to-schizophrenia/). In addition, our findings were presented at international scientific meetings including the Schizophrenia International Research Society (SIRS) 2018 conference, International Early Psychosis Association (IEPA) 2018 conference, and American College of Neuropsychopharmacology (ACNP) 2018 annual meeting.

In a follow-up study, we performed a prediction analysis to assess if functional brain connectivity and modular connectome organization are predictive of psychosis development. Using machine learning and leave-one-out cross-validation, we found that a prediction model that combined connectivity metrics with clinical and cognitive predictors yielded superior outcome prediction. This model outperformed connectivity-only and clinical-only prediction models. These findings were published in Neuroimage: Clinical and presented at the Society for Biological Psychiatry (SOBP) 2019 conference.

In addition, we had access to an independent dataset of children with a familial risk for serious mental illness because they had a parent or sibling diagnosed with schizophrenia or an affective psychotic disorder (i.e. bipolar disorder or psychotic depression). Using this dataset, we replicated our earlier findings that brain network disturbances predate illness onset. Moreover, we found that disturbances in functional brain networks that process self-relevant information were associated with behavioral precursors of future psychopathology, including internalizing problems, withdrawn behavior, and thought problems. These findings suggest that early interventions that target these specific networks may not only reduce early internalizing problems, but may also help avert the progression from early behavioral problems to mental illness in at-risk youth. This insight is thus of key interest to the development of neurobiologically-informed early interventions that seek to slow or prevent the development of serious mental illness. These findings were published in two separate papers in Schizophrenia Research (2020) and Frontiers in Psychiatry (2021), and will be presented at the upcoming SIRS 2021 conference.
This project's findings that abnormalities in the brain network connectivity and functional organization precede, and likely contribute to, psychotic symptom development in youth with early warning signs of impending psychosis increase our understanding of the neurobiology of emerging schizophrenia, and may promote the development of early detection and targeted intervention strategies. To date, there are no curative treatment options for schizophrenia and consensus in the field holds that early intervention is one of the most promising avenues for improving prognosis in schizophrenia spectrum disorders. Intervening early in the developing illness may not only prevent full-blown psychosis, but may also protect the social and cognitive development and well-being of youth prone to psychosis and thereby help them reach their full adult potential and mitigate the costs of serious mental illness to society as a whole.
Main findings of functional connectome analysis in the prelude to psychosis