Newswise — Patients in the early stages of psychosis respond to treatments differently than those who have developed a chronic version of the disorder. Understanding the neurobiological changes from early to chronic stages is essential for developing targeted prevention and treatment strategies. But how symptoms change during this transition—and what role the brain plays—is unclear.
Researchers at Yale School of Medicine (YSM) have now examined patients with early and chronic forms of psychosis to map symptom evolution and identify relevant brain networks. They published their findings in the journal .
“We are interested in how psychosis and psychiatric disorders develop,” says Maya Foster, first author of the study and a PhD student in the lab of , associate professor of radiology and biomedical imaging at YSM. “With this study, we looked at the underlying brain networks—regions that are functionally connected and work in coordination—to link brain areas to symptoms in patients with either early or chronic psychosis, and we assessed the similarities and differences between these networks.”
Treating psychosis
The cause of psychosis symptoms are not well understood but are broadly believed to result from disrupted or altered brain activity. What are known as “positive” symptoms of psychosis—in that they are added experiences healthy individuals don’t usually encounter—include hallucinations and delusions, while negative symptoms—or deficient versions of healthy experiences—include memory impairment, disorganized thinking, lack of motivation, and an inability to feel pleasure. Patients with psychosis often experience negative symptoms first. As their psychosis worsens, positive symptoms emerge.
Despite their shared symptom experiences, early and chronic cases respond to treatment differently.
“Studies show that patients have better prognoses if they get treatment early,” says Foster. “Chronic psychosis has higher incidences of relapse, and available treatments do not work as well.”
Previous studies suggest that early interventions reduce psychosis symptoms, but longitudinal studies that follow patients through the transition from early to chronic condition have not yet been done. Filling in this information gap could help clinicians more effectively treat patients.
To begin to address this gap, Foster and Scheinost examined two large-scale open source datasets to identify how symptoms evolve in patients with early or chronic psychosis. The Human Connectome Project Early Psychosis (HCP-EP) dataset contains information for early psychosis patients who present with symptoms within five years of data collection. The Strategic Research Program for Brain Sciences (SRPBS) Multi-disorder Connectivity dataset consists of patients with varying levels of symptom severity. The HCP-EP dataset contained information for 107 participants, which was compared with data from 57 healthy participants. The SRPBS dataset contained information for 123 participants, which was compared with that of 99 healthy participants.
Mapping brain networks to psychosis symptoms
To identify connectivity patterns in the brain that underpin psychosis symptoms, the team trained a machine learning model on functional magnetic resonance imaging data and symptom information collected from individuals with early or chronic psychosis.
The researchers found the model was able to predict positive and negative symptoms in both groups. The predictions for the chronic psychosis population were stronger, likely because of greater symptom burden.
While psychosis arises from a disruption across the whole brain, the team found the frontoparietal network played a critical role in both early and chronic psychosis. This region of the brain is involved in cognitive flexibility, cognitive control, and coordinating behaviors. According to Foster, negative symptoms may be linked to disruptions in in the frontoparietal network.
These findings provide a neurobiological reference point that could allow clinicians to track symptom-based brain networks as patients transition from early to chronic psychosis, say the researchers.
“If we can characterize brain differences to better understand symptoms, then we could potentially identify targets or biomarkers,” says Scheinost. “With more work, we might be able to predict transition points to monitor as you go along in treatment.”
Future research could track patients over time to uncover how the identified brain networks change throughout the lifespan of psychosis. This approach could inform treatment options to improve care and prevent worsening of symptoms.
Foster and Scheinost collaborated with psychiatrist , associate professor of psychiatry at YSM and coauthor of the study, to contextualize their findings. Other Yale authors include Jean Ye and .
The research reported in this news article was used data from the Human Connectome Project for Early Psychosis, sponsored by National Institutes of Health as part of human connectome initiative. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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