Trying to Test for Psychosis Risk
Most people think of the onset of psychosis as sudden, but there are often warning signs that precede an episode. Knowing what to look for provides the best opportunity for early intervention. Diagnosing psychosis—defined as a break from reality often in the form of hallucinations and/or delusions—is a complicated process, often requiring an extensive search of medical and family history, along with a physical examination to rule out physical causes such as epilepsy or drugs. If the cause is mental illness, doctors will often prescribe antipsychotics to relieve episodes and prevent reoccurrence. Yet there hasn’t been a test available for determining whether a person would be susceptible to psychosis before they experience a first episode. However, some preliminary research shows some promising results.
A study published in Schizophrenia Bulletin and led by University of North Carolina at Chapel Hill researchers represents an important step forward in the accurate diagnosis of people who are experiencing the earliest stages of psychosis. It reports initial results showing a blood test that, when used for people experiencing symptoms that are considered high risk for psychosis, identifies those who later went on to develop psychosis.
According to Diana O. Perkins, M.D., M.P.H., a professor of psychiatry in the UNC School of Medicine, the blood test used plasma samples to analyze inflammation, oxidative stress, hormones, and metabolism levels, and included a selection of 15 measures of immune and neuroendocrinal system imbalances as well as evidence of oxidative stress. The neuroendocrine system controls reactions to stress and regulates many body processes, including mood and emotions.
Using computer algorithms can help determine patterns found in people who are at high risk. “Modern, computer-based methods can readily discover seemingly clear patterns from nonsensical data. Added to that, scientific results from studies of complex disorders like schizophrenia can be confounded by many hidden dependencies,” said Clark D. Jefferies, Ph.D. is a bioinformatics scientist at the UNC-cased Renaissance Computing Institute (RENCI), and a co-author of the study. “Thus, stringent testing is necessary to build a useful classifier. We did that.”
So what does this mean? Since it’s been made clear that the patterns found in the high-risk individuals aren’t random occurrences, scientists can start recording them and work towards a method of counteracting imbalances. If these patterns continue to be confirmed in other groups of high-risk individuals, analytic procedures can start moving forward, hopefully helping in diagnosis.