Detecting schizophrenia before symptoms arise
Schizophrenia is a mental health disorder characterized by disrupted perceptions and thoughts. Symptoms can include delusions, hallucinations, and impaired cognitive abilities.
In the United States, schizophrenia affects an estimated 0.25–0.64 percent of the population. Often appearing in an individual’s late teens or early 20s, schizophrenia is highly disruptive, challenging to treat, and long-lasting.
Treatment is much more effective if doctors can diagnose the condition early. Currently, however, specialists cannot diagnose schizophrenia until an individual has had their first psychotic episode. At this point, an individual’s behavior can change dramatically, and they “may lose touch with some aspects of reality.”
Recently, a team of researchers decided to look in detail at patterns in neural activity. They hoped to identify a signature in how parts of the brain communicate that might predict onset.
Identifying subtle and unexpected patterns is challenging, and the task took the combined skills of researchers from a number of institutions. Those involved came from the Massachusetts Institute of Technology in Cambridge, the Beth Israel Deaconess Medical Center in Boston, MA, the Brigham and Women’s Hospital, also in Boston, and the Shanghai Mental Health Center in China.
They published their combined findings this week in the journal Molecular Psychiatry.
The first signs
Before someone experiences their first psychotic episode, there can be subtle changes in the way they think. For instance, they might switch topics abruptly when talking, or answer questions with seemingly irrelevant answers.
However, only about 1 in 4 people who display these symptoms go on to develop schizophrenia. The researchers wanted to find a way to predict who will go on to develop the condition with more accuracy.
Because the Shanghai Mental Health Center receives such a high volume of patients, it made the perfect base for the study. In total, the researchers identified 158 people aged 13–34 years old who displayed the early symptoms that often predict schizophrenia. They also analyzed 93 control participants who did not display this telltale behavior.
Using MRI scans, the study focused on resting state networks; these are interactions between regions of the brain that occur while a person is at rest and not engaged in any cognitive tasks.
One of the principal investigators, Susan Whitfield-Gabrieli, explains, “We were interested in looking at the intrinsic functional architecture of the brain to see if we could detect early aberrant brain connectivity or networks in individuals who are in the clinically high-risk phase of the disorder.”
Each participant had an MRI scan and then received a follow-up scan 1 year later. At the 1-year point, 23 of the 158 high-risk individuals had received a schizophrenia diagnosis.
By examining the 23 and comparing them with the other participants, the research team was able to identify patterns that only occurred in these individuals.
The superior temporal gyrus
One brain region that caught the investigators’ eye was the superior temporal gyrus. This region of the brain contains the primary auditory cortex and is important for processing sounds. Usually, it connects to areas involved in motor control and sensory perception.
In the participants who had psychotic episodes, the superior temporal gyrus connected differently, having more intimate relationships with limbic regions, which are important for emotion processing.
The study’s authors believe this might help explain why auditory hallucinations — hearing voices, for instance — are common in people with schizophrenia.
Lead author Guusje Collin says, “You can consider this pattern to be a risk factor. If we use these types of brain measurements, then maybe we can predict a little bit better who will end up developing psychosis, and that may also help tailor interventions.”
The scientists hope that, if we can detect these subtle changes in communication between brain regions at an earlier age, it might help us predict who is most at risk. And, the more we understand the nature of these changes, the more hope we have of reversing them.
“That really gets at the heart of how we can translate this clinically, because we can get in earlier and earlier to identify aberrant networks in the hopes that we can do earlier interventions, and possibly even prevent psychiatric disorders.”
The researchers are already carrying out similar studies, looking at a younger set of individuals. They are also carrying out further analyses on the brain scans they used in the current experiment, searching for additional differences in white matter connections.
Although this work is in its infancy, the benefits could be significant for those at high risk of developing schizophrenia.
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