Brain disorders affect millions of people in Europe and place a heavy burden on families, healthcare systems, and society as a whole. An estimated 179 million Europeans live with conditions such as autism, schizophrenia, depression, insomnia, or dementia. Together, these disorders cost nearly 800 billion euros each year, and this number is expected to rise sharply as the population ages. Despite their impact, most available treatments only reduce symptoms. They do not stop the progression of disease or address the underlying biological causes.
A key challenge is that brain disorders have a complex origin. Many different genetic and environmental factors contribute to risk, and each factor has only a small effect. As a result, two people with the same diagnosis may carry very different combinations of risk factors. Large genetic studies known as genome-wide association studies (GWAS) can detect these risk factors, but the findings are often hard to interpret. Small genetic effects are difficult to translate into biological insights, and even harder to turn into meaningful functional experiments or treatment strategies.
The goal of this ERC project was to close this gap between genetic discovery and biological understanding. In other words, we aimed to explain what the identified genetic risk factors actually mean for the biology of brain disorders. Achieving this required close collaboration between human genetics and neuroscience.
The project focused on three main objectives:
1. Develop and apply new computational methods to combine genetic results with brain-related biological data, allowing clearer interpretation of GWAS findings.
2. Develop and apply new algorithms to understand the genetic differences that exist within and between brain disorders, helping reveal why patients with the same diagnosis may differ at the genetic level.
3. Test whether human stem-cell–based models can be used to examine the functional effects of genetic risk factors, offering a path toward experimental follow-up of GWAS discoveries.
Across the project, we developed several new algorithms, improved widely used genetic analysis tools, and applied these methods to large datasets covering many brain-related traits, with notable advances for Alzheimer’s disease and schizophrenia. We also generated and analyzed human stem-cell–derived neuronal and astrocyte cultures and combined these findings with proteomics and post-mortem brain data. Together, these results provide new insight into the biological pathways affected in brain disorders, including those related to cell-type specificity, local genetic effects, and disease-related changes in neuronal and glial function.
In conclusion, the project successfully advanced the connection between genetic discoveries and brain biology. It delivers computational tools, biological findings, and experimental resources that help move the field closer to understanding the mechanisms behind brain disorders and, ultimately, toward improving treatment strategies.
