Researchers Identify Brain Abnormalities
in People with Schizophrenia
ATLANTA—Structural
brain abnormalities in patients with schizophrenia, providing insight into how
the condition may develop and respond to treatment, have been identified in an
internationally collaborative study led by a Georgia State University
scientist.
Scientists
at more than a dozen locations across the United
States and Europe
analyzed brain MRI scans from 2,028 schizophrenia patients and 2,540 healthy
controls, assessed with standardized methods at 15 centers worldwide. The
findings, published in Molecular Psychiatry,
help further the understanding of the mental disorder.
The
work was the outcome of the Enhancing Neuroimaging Genetics through
Meta-Analysis project (ENIGMA), from the Schizophrenia Working Group that is
co-chaired by Jessica Turner, associate professor of
psychology and neuroscience at Georgia
State , and Theo van Erp, assistant
research professor in psychiatry at the University
of California , Irvine .
“This
is the largest structural brain meta-analysis to date in schizophrenia, and
specifically, it is not a meta-analysis pulled only from the literature,” said
Turner. “Investigators dug into their desk drawers, including unpublished data
to participate in these analyses. Everyone performed the same analyses using
the same statistical models, and we combined the results. We then identified
brain regions that differentiated patients from controls and ranked them
according to their effect sizes.”
The
team found individuals with schizophrenia have smaller volume in the
hippocampus, amygdala, thalamus, nucleus accumbens and intracranial space than
controls, and larger pallidum and ventricle volumes. The study validates
collaborative data analyses can be used across brain phenotypes and disorders,
and encourages analysis and data-sharing efforts to further understanding of
severe mental illness.
The
ENIGMA collaborations include working groups for other disorders such as
bipolar disorder, attention deficit, major depression, autism and addictions,
who are all doing these same analyses.
The
next step in this research is to compare the effects across disorders, to
identify which brain region is the most affected in which disorder, and to
determine the effects of age, medication, environment and symptom profiles across
these disorders.
“There’s
the increased possibility, not just because of the massive datasets, but also
because of the collaborative brain power being applied here from around the
world, that we will find something real and reliable that will change how we
think about these disorders and what we can do about them,” Turner said.
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