Researchers from the Yong Loo Lin School of Medicine, National University of Singapore (NUS Medicine), and NHG Health's Institute of Mental Health (IMH) have mapped how brain networks differ in individuals at Clinical High Risk (CHR) for psychosis , providing a new perspective on the mechanisms underlying the disease onset. Published in Molecular Psychiatry , the study utilised advanced neuroimaging methods to identify early, network-level changes in more than 3,000 individuals at varying levels of risk.
The study – led by Dr Siwei Liu, Senior Research Scientist, and Associate Professor Juan Helen Zhou, Director, both at the Centre for Translational Magnetic Resonance Research (TMR), NUS Medicine, and in collaboration with Associate Professor Jimmy Lee, Senior Consultant Psychiatrist and Clinician-Scientist at IMH – sought to determine how brain networks can reveal signs in young individuals with heightened clinical risk of developing psychosis.
Using data from the Enhancing Neuro Imaging Genetics by Meta-Analysis-Clinical High Risk (ENIGMA-CHR) working group, the team analysed brain scans from over 3,000 participants aged between 9.5 and 39.9 years across 31 global sites, including Singapore. The local data came from IMH's Longitudinal Youth-At-Risk Study (LYRIKS), which was initiated in 2008 and led by Assoc Prof Lee, to identify clinical, social, neuropsychological and biological risk factors unique to individuals at high risk of developing psychosis.
The study compared the brain network patterns between young people at high risk for psychosis and healthy individuals, as well as between those who later developed psychosis and those who did not. Using graph theory-based network analysis, they mapped how different brain regions communicate structurally. This approach treats the brain as a complex network, where nodes represent regions and edges represent their connections.
The team observed that in a healthy brain, regions that develop and work together form networks that balance strong local connections with efficient communication across areas. Regional neighbours share both direct and indirect connections, supporting effective local processing. Even with minor damage in one region, neighbouring regions can still communicate through alternate paths. Efficient long-range communication means that even far-apart regions can exchange information quickly using only a few steps.
However, the study found that individuals at high risk for psychosis had less efficiently organised brain networks than healthy individuals. This organisation makes local processing less effective and integrative processing across the brain more difficult. Differences in frontal and temporal brain areas were also linked to whether an individual developed psychosis later in life and how severe their symptoms were, suggesting that brain network patterns may play an important role in the transition to psychosis. The findings also indicated that individuals at high risk for psychosis exhibited early disruptions in the organisation of brain networks, despite showing only mild clinical symptoms.
"Treating the brain as a complex network has allowed us to capture subtle but meaningful differences in communication pathways," said Dr Liu, first author of the paper. "These findings highlight the potential of brain imaging to detect early alterations and how early changes in network structure may contribute to the onset of psychotic symptoms." Dr Liu is also a Senior Research Scientist at the Centre for Sleep and Cognition, NUS Medicine.
Assoc Prof Zhou, corresponding author of the paper, added, "This study underscores that psychosis is not a sudden event but a progressive process reflected in the brain's communication networks. Individuals at high clinical risk already show distinctive patterns of reduced integration and local efficiency. Understanding these patterns gives us an opportunity to identify at-risk individuals earlier and with greater precision. Ultimately, integrating such imaging-based insights into clinical assessment could improve prognosis and allow for timely and preventive therapies." Assoc Prof Zhou is also a Principal Investigator at the Centre for Sleep and Cognition, NUS Medicine.
Other collaborators of the study include Dr Maria Jalbrzikowski and Dr Dennis Hernaus, who chair the ENIGMA-CHR working group. Dr Jalbrzikowski is from the Department of Psychiatry and Behavioural Sciences, Boston Children's Hospital, United States of America, and Dr Hernaus is from the Department of Psychiatry and Neuropsychology, Mental Health and Neuroscience Research Institute, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands.
"This study represents a significant step forward in understanding the biological trajectory of psychosis," said Assoc Prof Lee. "By examining nearly 3,000 young people across multiple sites, we now have robust evidence that brain network disruption follows predictable patterns years before clinical symptoms fully emerge. This isn't about finding a single faulty brain region, but understanding how the brain's systems gradually become less coordinated, which opens a crucial window for early intervention that we've never had before. Being able to identify possible onset of psychosis early would allow us to intervene before symptoms take hold, improve long-term outcomes and reduce the impact of psychosis on young people's lives."
The study also suggests that the brains of young people at high risk for psychosis may be more vulnerable to certain types of damage, as observed in the reduced local backup connections and longer route between distant regions in the study. Young people at high risk for psychosis often face social difficulties, additional mental health issues, and a lower quality of life, creating a significant burden on them. [1] Preventive interventions could help ease this burden and possibly reduce the risk of progressing into fully developed psychosis.
The study enhances understanding of how psychosis may develop through interconnected brain pathways, supporting the hypothesis that tissue damage can spread across these networks. This underscores the importance of studying brain organisation to better trace the disease process. Building on these findings, the researchers plan to explore brain network patterns further with the goal of identifying biomarkers that could eventually support early detection and targeted interventions to lessen the long-term impact of psychosis.
[1] https://www.healthhub.sg/programmes/mindsg/caring-for-ourselves/understanding-psychosis-youths#psychosis-container
