Schizophrenia’s core genetic features proposed

Schizophrenia’s elusive genetic roots may finally be within grasp. A new, wide-ranging effort has uncovered a set of DNA signatures that are shared by people with the disease consistently enough that the set can be used to reliably predict whether someone has the disease. If replicated, the results may point out ways to diagnose schizophrenia and suggest new targets for treatment.

By analyzing a battery of 542 genetic variants, researchers could predict who had schizophrenia in a group of European Americans and African Americans. The confirmation of the result in people of varying ancestry suggests that the set of genes truly does detect the core features of the disorder, scientists report online May 15 in Molecular Psychiatry.

“Genetic studies in psychiatry tend to produce initial excitement but are then not reproduced in independent populations, which is the most important proof that a finding is solid and real,” says study coauthor Alexander Niculescu of the Indiana University School of Medicine in Indianapolis.

Niculescu and his colleagues created their gene panel by assessing a slew of earlier studies on schizophrenia: Data from humans and animals on gene variation and gene behavior all fed into the team’s analysis. If a gene popped out of several different datasets, the reasoning went, it is probably important to schizophrenia. Niculescu compares this method — called convergent functional genomics — to an Internet search: “The more links to a web page, the higher it comes up on your search list.”

After sifting through all of this data, the team identified some top candidates, some already known to be related to schizophrenia (DISC1, a known culprit, sits at the top of the list) and a handful that have never before been linked to the disease.

“This is an interesting attempt at integrating data,” says Pablo Gejman of NorthShore University Health System in Evanston, Ill. and the University of Chicago. But the results come with many caveats, he says: Integrating a wide variety of data generated in earlier experiments can be problematic. Earlier studies may have been testing specific ideas that may not be relevant to the current study, and earlier negative results may have been overlooked, for instance. It’s too soon to say what the results really mean, he says. “It’s evolving science, and I don’t know where it will go.”