New Understanding of Genes Leads to Better Predictive Test for Schizophrenia

By categorizing a group of genes previously associated with schizophrenia and assigning them priority based on their effect on the odds of developing the disease, a team from Indiana University has developed a predictive score that may be used to detect at-risk patients. The complete study has been published in the journal Molecular Psychiatry.

The group used a method called convergent functional genomics to integrate a number of disparate experimental techniques into a single score, which they then applied to participants in past studies. They were able to successfully identify which of those participants went on to develop schizophrenia. The predictions made by the score were not 100 percent accurate, but they were statistically significant.

The proposed score is contingent on the view of schizophrenia as a disease arising from many factors, including genetic variation and its effect on neurodevelopmental connections, and on environmental factors like stress. The score purports to identify those at risk genetically and then correct for the effects of environment on those susceptible to the disease. It is also useful for showing that schizophrenia risk is not an either-or condition, but rather that it falls on a continuum.

While not intended to be a stand-alone diagnostic tool, when taken in combination with behavioral observation and other current diagnostic methods, the Indiana score will aid researchers and clinicians in providing early intervention and treatment.

Source: Indiana University

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