A Brain Signal for Psychosis Risk

Reports new study in Biological Psychiatry
Mar 13, 2014 11:00 AM ET

Philadelphia, PA, March 13, 2014 /3BL Media/ – Only one third of individuals identified as being at clinical high risk for psychosis actually convert to a psychotic disorder within a 3 year follow-up period. This risk assessment is based on the presence of sub-threshold psychotic-like symptoms.

Thus, clinical symptom criteria alone do not predict future psychosis risk with sufficient accuracy to justify aggressive early intervention, especially with medications such as antipsychotics that produce significant side effects.

Accordingly, there is a strong imperative to develop biomarkers of psychosis risk that can improve the ability to predict which individuals are most likely to transition to a psychotic disorder.

A study published in the current issue of Biological Psychiatry provides evidence that mismatch negativity (MMN), an event-related brain potential component derived from scalp electroencephalography (EEG) recordings, may be such a biomarker.

Mismatch negativity is an EEG signal that is elicited automatically from auditory cortex and frontal lobe regions of the brain in response to sounds that deviate from preceding sounds in pitch, duration, or other auditory features, even when one is not paying attention to the sounds. This electrophysiological measure of auditory deviance detection is thought to reflect short term plasticity in the brain, since it depends on the formation of a short term memory of recently heard sounds in order to detect a deviant sound.

Mismatch negativity is known to be reduced in patients with full-blown schizophrenia. So, to conduct this study, researchers assessed MMN in patients with schizophrenia, patients at clinical high risk for psychosis, and healthy control subjects. Compared to the healthy subjects, MMN was reduced in the patients with schizophrenia, as expected, but was also reduced in the high-risk patients. Analyses showed that MMN did not differ between the two patient groups.

“Our study results show that mismatch negativity deficits precede the onset of psychosis in clinical high risk individuals, and further shows that the larger the deficit, the more imminent the risk for conversion to a psychotic disorder,” said Dr. Daniel Mathalon, Professor of Psychiatry at the University of California, San Francisco and senior author on the paper.

In addition, they also followed the clinical high-risk group for over twelve months and compared those who converted to a psychotic disorder with those who did not. MMN was reduced in those individuals who ultimately developed a psychotic disorder, compared to those who remained only in the clinical high risk category.

Mathalon added, “Importantly, our study results converge with those reported by several other studies from researchers in Europe and Asia. This remarkable convergence of findings points to the mismatch negativity as a promising EEG-based biomarker of psychosis risk that, with further development, could enhance our ability to identify which individuals are at greatest risk for psychosis and in greatest need of early treatment, particularly if the treatment is associated with potential adverse effects (such as antipsychotic medication).”

Indeed, there is substantial interest in developing diagnostic and prognostic tests for psychiatric disorders. “We do not currently use tests to help us make diagnoses or to inform patients about the likely long-term course of their illness,” commented Dr. John Krystal, Editor of Biological Psychiatry. “However, this study suggests that one day it may be possible to develop this type of test.”

The article is “Automatic Auditory Processing Deficits in Schizophrenia and Clinical High-Risk Patients: Forecasting Psychosis Risk with Mismatch Negativity” by Veronica B. Perez, Scott W. Woods, Brian J. Roach, Judith M. Ford, Thomas H. McGlashan, Vinod H. Srihari, and Daniel H. Mathalon (doi: 10.1016/j.biopsych.2013.07.038). The article appears in Biological Psychiatry, Volume 75, Issue 6 (March 15, 2014), published by Elsevier.

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Notes for editors
Full text of the article is available to credentialed journalists upon request; contact Rhiannon Bugno at +1 214 648 0880 or Biol.Psych@utsouthwestern.edu. Journalists wishing to interview the authors may contact Dr. Daniel Mathalon at +1 415 221 4810, ext. 3860 or daniel.mathalon@ucsf.edu.

The authors’ affiliations, and disclosures of financial and conflicts of interests are available in the article.

John H. Krystal, M.D., is Chairman of the Department of Psychiatry at the Yale University School of Medicine, Chief of Psychiatry at Yale-New Haven Hospital, and a research psychiatrist at the VA Connecticut Healthcare System. His disclosures of financial and conflicts of interests are available here.

About Biological Psychiatry
Biological Psychiatry is the official journal of the Society of Biological Psychiatry, whose purpose is to promote excellence in scientific research and education in fields that investigate the nature, causes, mechanisms and treatments of disorders of thought, emotion, or behavior. In accord with this mission, this peer-reviewed, rapid-publication, international journal publishes both basic and clinical contributions from all disciplines and research areas relevant to the pathophysiology and treatment of major psychiatric disorders.

The journal publishes novel results of original research which represent an important new lead or significant impact on the field, particularly those addressing genetic and environmental risk factors, neural circuitry and neurochemistry, and important new therapeutic approaches. Reviews and commentaries that focus on topics of current research and interest are also encouraged.

Biological Psychiatry is one of the most selective and highly cited journals in the field of psychiatric neuroscience. It is ranked 4th out of 135 Psychiatry titles and 13th out of 251 Neurosciences titles in the Journal Citations Reports® published by Thomson Reuters. The 2012 Impact Factor score for Biological Psychiatry is 9.247.

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