To determine the biological basis of mental disorders such as schizophrenia and depression, scientists have tried many technical approaches — each with their own strengths and weaknesses.
For example, genetic association studies of psychiatric disorders have located gene variants associated with the disorders, but have been able to explain only a small percentage of their heritability. Researchers have also collected detailed clinical records on psychiatric patients and the efficacy and side effects of available treatments, but the potentially valuable information within those records remains largely untapped.
Rather than focusing on just one of these methods, the Conte Center will apply computational analysis to data from all of them to discover new network relationships between genes, environmental factors, and clinical phenotypes. The results will create novel, testable hypotheses that could alter how experts define and treat neuropsychiatric disorders.
“There’s more data than we know what to do with at this point,” said Edwin H. Cook Jr., professor of psychiatry at the University of Illinois at Chicago. “The analytic, informational and data management approaches in this very forward-thinking Conte Center should allow us to find things that we couldn’t before.”
Neuropsychiatric disorders are particularly well suited for this approach, due to the hazy diagnostic and biological borders between conditions. A 2007 study by Rzhetsky and colleagues that applied statistical modeling methods to patient records alone found a significant overlap between autism, schizophrenia, and bipolar disorder that implied a genetic relationship.
“Most studies are done one disorder at a time, and that’s like studying the trunk or the hoof or the tail of an elephant; you might miss the big picture,” said Benjamin Lahey, the Irving B. Harris Professor of Epidemiology at UChicago. “This project will enable us to look at things in a way that has never been done before, at a scale that dwarfs anything that’s ever been done.”
Russ Altman, professor of bioengineering, genetics and medicine at Stanford University, said, “Diagnosis and treatment of these disorders is incredibly challenging. These data-driven approaches have a real chance to uncover new models for not only the pathogenesis of the individual diseases, but perhaps even a new way to think about the constellation of related diseases.”
The center will operate similarly to a “large software project,” the investigators said, with four simultaneous projects and three core centers working in parallel to produce integrated results. An advanced, cloud-based computing system will be used to share data among investigators and with the public.
The data-mining efforts will generate models of the interaction between genes, environmental factors, and phenotypes that can then be tested in collaboration with the Institute for Genomics and Systems Biology at the University of Chicago.
“The molecular basis for diseases such as autism, schizophrenia and bipolar disorder has been tremendously difficult to resolve,” said Kevin White, the James and Karen Frank Family Professor of Ecology & Evolution and director of the IGSB. “By bringing together experts from multiple domains, from computational biologists to clinicians, the team Rzhetsky has assembled will be focusing on high-risk, high-reward research in an attempt to propel the field forward.”
If successful, the approach of mining existing data from several different methods could potentially be applied to other types of disorders, including the overlap between mental and physical disorders such as schizophrenia and diabetes.
“We definitely have one of the strongest genomics groups in the country, we have probably one of the strongest statistical genetics groups, and we have excellent world-renowned experts in phenotypes,” Rzhetsky said. “It’s exciting because there is potential, but now we have to work hard to get there.”