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MRI may predict who is at risk for developing schizophrenia

by Lisa Chamoff, Contributing Reporter | May 18, 2015
MRI
MRI scans that map the wiring of the brain could help predict whether people are at risk of developing schizophrenia, a new study has found.

“Dysconnectivity” in the brain has generally been considered a hallmark of schizophrenia, which causes hallucinations and delusions. Researchers from Cardiff University Brain Research Imaging Centre (CUBRIC), the Institute of Psychiatry, Psychology and Neuroscience at Kings College London, and the University of Bristol used diffusion-weighted MRI to reconstruct the interconnections of the brain in individuals with less severe forms of the condition. The study was published online in the journal Human Brain Mapping.

The team scanned 123 people who have had psychotic experiences and a control group of 125 people who had not. For the people who showed signs of vulnerability to schizophrenia, the researchers saw a reduction in the ability to transfer information from one part of the brain to another, particularly in core network hubs.
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The study used an approach called graph theory, which, according to the study, is “a powerful mathematical framework that quantifies topological features of networks.”

Dr. Mark Drakesmith, a researcher at CUBRIC and the lead study author, said that in looking at the overall architecture of the network of the brain, the study shows very similar network differences in individuals with some signs of vulnerability to schizophrenia, which suggests that these changes are present much earlier than when the full illness manifests.

“The approach is still a long way off being a clinically feasible diagnostic tool, but these findings take us a step closer,” Drakesmith told DOTmed News.

The next step for the researchers is to identify which of the subjects transitioned to full schizophrenia and see what the brain networks of these individuals looked like before they became ill, Drakesmith said. “That will give us an even clearer picture of network features to look out for as a predictor of illness.”

Drakesmith noted that another study has found that first-degree relatives of people with schizophrenia share similar network features, and researchers at CUBRIC are also looking at network organization in healthy carriers of schizophrenia risk genes.

“The hope is that in future, network organization will let us identify vulnerability to schizophrenia more accurately than the presence of other risk factors, such as family history,” Drakesmith said.

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