Scientists have long known that schizophrenia runs in families, but pinpointing exactly which genes contribute to risk has been like searching for needles in a haystack. Now, researchers at the Lieber Institute for Brain Development and a consortium of collaborators from the University of Bari, Italy, and over 60 psychiatric hospitals all over the world, have developed a groundbreaking approach that looks beyond individual genes. They have uncovered how networks of genes communicate across the brain – revealing 641 previously unrecognized genes associated with schizophrenia.
The study, published in Nature Genetics, analyzed genetic data from over 102,000 individuals and brain tissue samples from hundreds of donors across six different brain regions. Traditional methods to associate genes with diseases only examine variants in the immediate proximity of the genes considered. However, the field is aware that the lion’s share of genes’ involvement in a disease depends on long-distance variants. The research team developed new computational models that capture long-range regulatory relationships among genes – similar to how social networks connect people who don’t live next door to each other. This enhanced modeling framework enabled the discovery of hundreds of schizophrenia-associated genes that would not have been detected otherwise.
Most genetic studies have been looking for the light under the lamppost, focusing only on genes close to disease-associated DNA variants. By incorporating gene co-expression networks, we’ve essentially turned on lights across the entire neighborhood, revealing how distant genetic variants coordinate to build the genetic basis of schizophrenia.”
Dr. Giulio Pergola, senior author and researcher, Lieber Institute for Brain Development
The findings point to biological pathways involved in glutamate signaling, brain-cell communication, immune processes, and brain development – pathways that may help guide future research into new treatment strategies.
“This work demonstrates that schizophrenia risk isn’t just about individual genes acting one after another – it’s about how networks of genes work together,” said Dr. Daniel Weinberger, CEO and Director of the Lieber Institute for Brain Development. “Understanding these coordinated genetic programs brings us closer to precision psychiatry, where treatments can be tailored to an individual’s specific biological profile.”
The research represents a significant advance in translating genetic discoveries into actionable biological insights for one of psychiatry’s most burdensome disorders.
Source:
Lieber Institute for Brain Development
Journal reference:
Rossi, F., et al. (2026). Co-expression-based models improve eQTL predictions for transcriptome-wide association studies and highlight new schizophrenia-associated genes. Nature Genetics. DOI: 10.1038/s41588-026-02646-3. https://www.nature.com/articles/s41588-026-02646-3