Groundbreaking Study Maps Brain Network Differences in Individuals at Risk of Psychosis
New research from Singapore and international collaborators reveals early brain changes detectable years before the onset of psychotic symptoms, offering a crucial window for preventative intervention.
A landmark study has mapped how brain networks differ in young individuals at Clinical High Risk (CHR) for psychosis, providing a new perspective on the biological mechanisms underlying the development of this serious mental illness. Published in Molecular Psychiatry in July 2025, the research utilized advanced neuroimaging to identify subtle, network-level changes in over 3,000 participants across varying levels of risk.
The study, spearheaded by researchers from the Yong Loo Lin School of Medicine, National University of Singapore (NUS Medicine), and NHG Health’s Institute of Mental Health (IMH), represents a significant step toward early detection and targeted therapies. Led by Dr. Siwei Liu, Senior Research Scientist, and Associate Professor Juan Helen Zhou, Director, 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, the investigation sought to understand how brain network patterns could signal the emergence of psychosis in young people.
Researchers analyzed brain scans from participants aged 9.5 to 39.9 years, drawing data from the Enhancing Neuro Imaging Genetics by Meta-Analysis-Clinical High Risk (ENIGMA-CHR) working group, encompassing 31 global sites including Singapore. Local data originated from IMH’s Longitudinal Youth-At-Risk Study (LYRIKS), initiated in 2008 by Assoc Prof Lee, which focuses on identifying unique clinical, social, neuropsychological, and biological risk factors for psychosis.
The team employed graph theory-based network analysis to map structural communication between different brain regions, treating the brain as a complex network of interconnected nodes and edges. In a healthy brain, these networks exhibit a balance of strong local connections and efficient long-range communication, allowing for robust information processing even in the face of minor regional damage.
However, the study revealed that individuals at high risk for psychosis exhibited significantly less efficient brain network organization. “Treating the brain as a complex network has allowed us to capture subtle but meaningful differences in communication pathways,” explained Dr. Liu, first author of the paper. This disrupted organization hinders both local processing and integrative processing across the brain.
Specifically, differences in the frontal and temporal brain areas were linked to both the development of psychosis and the severity of symptoms, suggesting a critical role for these network patterns in the transition to the illness. Importantly, the study found evidence of these disruptions even in individuals exhibiting only mild clinical symptoms.
“This study underscores that psychosis is not a sudden event but a progressive process reflected in the brain’s communication networks,” added Assoc Prof Zhou, corresponding author. “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.”
The research also suggests that the brains of young people at risk may be more vulnerable to damage, exhibiting fewer local backup connections and longer communication routes between distant regions. This vulnerability is particularly concerning given that individuals at high risk often experience social difficulties, co-occurring mental health issues, and a diminished quality of life.
According to Associate Professor Jimmy Lee, this research isn’t about pinpointing a single faulty brain region, but rather understanding how the brain’s systems become less coordinated over time. This realization opens a “crucial window for early intervention that we’ve never had before,” potentially allowing clinicians to intervene before symptoms fully manifest, improving long-term outcomes and lessening the impact of psychosis on young lives.
Building on these findings, the researchers plan to further explore brain network patterns to identify biomarkers that could support early detection and targeted interventions. This ongoing work underscores the importance of studying brain organization to better trace the disease process and develop more effective strategies for prevention and treatment. .
The study highlights the potential for preventive interventions to ease the burden on young people at risk and potentially reduce the likelihood of progressing to full-blown psychosis. This research represents a paradigm shift in our understanding of psychosis, moving beyond a focus on symptoms to a deeper understanding of the underlying biological trajectory.
Source: National University of Singapore, Yong Loo Lin School of Medicine
Journal reference: Liu, S., et al. (2025). Structural covariance network topology in individuals at clinical high risk for psychosis: the ENIGMA-CHR Study. Molecular Psychiatry. doi: 10.1038/s41380-025-03304-6. https://www.nature.com/articles/s41380-025-03304-6
