Blood Test May Help Determine Who Is at Risk for Psychosis

For individuals facing the possibility of a lifetime on antipsychotic medications, this new analysis may help them and their health care providers in making a difficult decision.

A study 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.

Psychosis includes hallucinations or delusions that define the development of severe mental disorders such as schizophrenia. Schizophrenia emerges in late adolescence and early adulthood and affects about 1 in every 100 people. In severe cases, the impact on a young person can be a life compromised, and the burden on family members can be almost as severe.

The study published in the journal Schizophrenia Bulletin reports preliminary results showing that a blood test, when used in psychiatric patients experiencing symptoms that are considered to be indicators of a high risk for psychosis, identifies those who later went on to develop psychosis.

“The blood test included a selection of 15 measures of immune and hormonal system imbalances as well as evidence of oxidative stress,” said Diana O. Perkins, MD, MPH, professor of psychiatry in the UNC School of Medicine and corresponding author of the study. She is also medical director of UNC’s Outreach and Support Intervention Services (OASIS) program for schizophrenia.

The image shows a person testing a blood sample from a test tube.
The study concludes that the multiplex blood assay, if independently replicated and if integrated with studies of other classes of biomarkers, has the potential to be of high value in the clinical setting. This image is for illustrative purposes only. Credit PublicDomainPictures.

“While further research is required before this blood test could be clinically available, these results provide evidence regarding the fundamental nature of schizophrenia, and point towards novel pathways that could be targets for preventative interventions,” Perkins said.

Clark D. Jeffries, PhD, bioinformatics scientist at the UNC-based Renaissance Computing Institute (RENCI), is a co-author of the study, which was conducted as part of the North American Prodrome Longitudinal Study (NAPLS), an international effort to understand risk factors and mechanisms for development of psychotic disorders.

“Modern, computer-based methods can readily discover seemingly clear patterns from nonsensical data,” said Jeffries. “Added to that, scientific results from studies of complex disorders like schizophrenia can be confounded by many hidden dependencies. Thus, stringent testing is necessary to build a useful classifier. We did that.”

The study concludes that the multiplex blood assay, if independently replicated and if integrated with studies of other classes of biomarkers, has the potential to be of high value in the clinical setting.

Notes about this psychiatry research

Contact: Tom Hughes – UNC Health Care
Source: UNC Health Care press release
Image Source: The image is credited to PublicDomainPictures and is in the public domain
Original Research: Abstract for “Towards a Psychosis Risk Blood Diagnostic for Persons Experiencing High-Risk Symptoms: Preliminary Results From the NAPLS Project” by Diana O. Perkins, Clark D. Jeffries, Jean Addington, Carrie E. Bearden, Kristin S. Cadenhead, Tyrone D. Cannon, Barbara A. Cornblatt, Daniel H. Mathalon, Thomas H. McGlashan, Larry J. Seidman, Ming T. Tsuang, Elaine F. Walker, Scott W. Woods and Robert Heinssen Schizophrenia Bulletin. Published online August 10 2014 doi:10.1093/schbul/sbu099

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  1. *May* help predict? Why don’t they wait until they have actual proof until they report something?

    In addition,

    1) Many people are not helped by so-called antipsychotics

    2) Some people recover without them (John Nash for example, whose story was misrepresented in “A Beautiful Mind”)

    3) Some people who do take them don’t necessarily take them for the rest of their lives

    4) Medical journals in general have an extremely strong bias in selecting articles to publish (oftentimes results aren’t replicable, but no one wants to read articles about things that *don’t* work)

    The list goes on…

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