Similar to people, a lot can be learned about a gene by looking at the company it keeps and watching how it behaves. In an effort to uncover more clues about the development of schizophrenia, researchers at the University of Pittsburgh School of Medicine explored how the proteins produced by schizophrenia-related genes interacted with one another.
“We can infer what the protein might do by checking out the company it keeps,” said senior investigator Madhavi Ganapathiraju, Ph.D., assistant professor of biomedical informatics, Pitt School of Medicine.
“For example, if I know you have many friends who play hockey, it could mean that you are involved in hockey, too. Similarly, if we see that an unknown protein interacts with multiple proteins involved in neural signaling, for example, there is a high likelihood that the unknown entity also is involved in the same.”
In recent history, scientists have conducted many genome-wide association studies (GWAS) that have successfully identified gene variants tied to an increased risk for schizophrenia. However, relatively little is known about the proteins that these genes make, what they do and how they interact, say the researchers.
“GWAS studies and other research efforts have shown us what genes might be relevant in schizophrenia,” said Ganapathiraju. “What we have done is the next step. We are trying to understand how these genes relate to each other, which could show us the biological pathways that are important in the disease.”
In a nutshell, each gene makes proteins, and these proteins typically interact with each other in a biological process. Studying how these proteins behave with one another can shed light on the role of a gene that has not yet been studied, revealing pathways and biological processes associated with schizophrenia as well as its relation to other complex diseases.
After developing and using a new computational model, called High-Precision Protein Interaction Prediction (HiPPIP), the researchers discovered more than 500 new protein-protein interactions (PPIs) associated with genes linked to schizophrenia.
The researchers add that while schizophrenia-linked genes identified historically and through GWAS had little overlap, the model showed they shared more than 100 common interactors. The findings could lead to greater understanding of the biological underpinnings of this mental illness, as well as point the way to treatments.
The findings are published online in npj Schizophrenia, a Nature Publishing Group journal.