Scientists Discover Neural Basis of Schizophrenia and Bipolar Disorder
By Roberto Molar Candanosa, Johns Hopkins University, December 20, 2025, 8 Comments,
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Using lab-grown brain tissue, researchers uncovered complex patterns of neural signaling that differ subtly between healthy brains and those linked to severe psychiatric disorders.
For the first time, scientists have used pea-sized brain organoids grown in the laboratory to uncover how neurons may malfunction in schizophrenia and bipolar disorder. These psychiatric conditions affect millions of people around the world, yet they remain difficult to diagnose because researchers still lack a clear understanding of their underlying molecular mechanisms.
The results could eventually help clinicians reduce diagnostic uncertainty when treating these and other mental health conditions. At present, such disorders are typically identified through clinical judgment alone, and treatment often relies on lengthy trial-and-error approaches to medication.
A detailed account of the findings was published in the journal APL Bioengineering.
“Schizophrenia and bipolar disorder are very hard to diagnose because no particular part of the brain goes off. No specific enzymes are going off like in Parkinson’s, another neurological disease where doctors can diagnose and treat based on dopamine levels even though it still doesn’t have a proper cure,” said Annie Kathuria, a Johns Hopkins University biomedical engineer who led the research. “Our hope is that in the future we can not only confirm a patient is schizophrenic or bipolar from brain organoids, but that we can also start testing drugs on the organoids to find out what drug concentrations might help them get to a healthy state.”
Machine learning decodes disease specific signals
Kathuria’s team created the organoids, simplified versions of brain tissue, by reprogramming blood and skin cells from people with schizophrenia, bipolar disorder, and from healthy volunteers into stem cells capable of forming brain-like structures. They then applied machine learning tools to analyze the electrical activity of the organoids’ cells, allowing them to identify neural firing patterns associated with healthy and diseased states. In the human brain, neurons communicate through small electrical signals.
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