ORLANDO, Florida — Slowed processing and identification of facial emotions appears to predict conversion to full-blown schizophrenia in high-risk youth with prodromal psychotic symptoms, new research shows.
The finding of slower reaction times in converters, especially delays in verbal identification of emotions, suggests language disturbance may underlie this association, a finding that suggests testing for reaction times may help predict which patients are at greatest risk of developing schizophrenia.
“That is the holy grail — to stop kids from converting. The more we know about predictive factors, the more we hope to find ways to prevent that from happening. That is the holy grail for me,” said presenter Zarina R. Bilgrami, BA, project coordinator for the Program in Psychosis Risk at the Icahn School of Medicine at Mount Sinai, New York City.
The study‘s senior investigator, Cheryl Corcoran, MD, Icahn School of Medicine at Mount Sinai and James J. Peters VA Medical Center, has researched the prodromal phase that precedes schizophrenia onset and has identified those at clinical high risk (CHR).
Individuals who fall into the clinical high risk category include those with attenuated psychotic symptoms, said Bilgrami.
“For example, instead of having hallucinations, a person might hear their name in the wind, or see shadows out of the corner of their eye. These people are also very mistrustful and suspicious. Yet they still have insight into the fact that perhaps their mind is playing tricks on them, rather than having what we call a ‘full-blown’ psychiatric disorder where there is complete delusion and hallucinations,” she told Medscape Medical News.
For the study, investigators examined reaction times for face processing in seven CHR youths who went on to convert to schizophrenia, 31 healthy controls, and 42 CHR youths who did not convert. They used the UPenn battery — a group of tests that include the Emotion Recognition (ER-40); Emotion Discrimination (EMODIFF), Emotional Acuity, and Facial Identification tests.
“We wanted to zero in on this population because we want to refine our understanding of what causes or allows these people to progress,” Bilgrami said.
Compared with nonconverters and healthy controls, converters had a significantly slower reaction time for face emotion recognition (P = .008) when shown the face of an angry man.
There were no other differences between the three groups with respect to emotion discrimination, acuity, or facial identification.
The predictive emotion recognition test required individuals to first name the emotion they were seeing, and then click on the correct answer from a list of possible emotions.
“They have to delve into their lexicon to come up with the right word to name the emotion. Then they have to make a choice from a list, and click. So when they see an emotion in someone’s face, there is a significantly slower response in the people who go on later to develop a psychotic disorder. We’re able to see this before it actually happens, based on this task,” Bilgrami said.
Motor praxis, the ability to move the mouse and click, was also significantly slower in converters than in healthy controls and nonconverters (P < .001).
“The aim of this is to catch people as early as possible. We’ve been studying the duration of untreated psychosis [DUP], and if you minimize that duration, the better the prognosis is in the long run. So if we can catch people really early and keep tabs on them we can minimize the DUP. That is the hope of our research,” she said.
Opportunity for Early Intervention
Commenting on the findings for Medscape Medical News, Deanna L. Kelly, PharmD, professor of psychiatry at the University of Maryland School of Medicine in Baltimore and director of the Treatment Research Program at the Maryland Psychiatric Research Center, said the ability to predict which patients will develop schizophrenia among CHR patients helps provide earlier interventions and treatment and potentially alter the course of disease onset.
“This group [of researchers] found that among patients at clinically high risk, those who developed schizophrenia had significantly slower reaction time for recognizing emotions with facial expressions,” said Kelly, who was not involved with the current research.
“The task used to identify emotions entails the verbal identification of emotions, suggesting an underlying association with a language disturbance consistent with other work from this group. Accumulating evidence suggests that linguistic features may provide a way to predict those at risk for developing schizophrenia,” she said.
The study was funded by the National Institutes of Health. Belgrami has disclosed no relevant financial relationships. Kelly reports she served as a consultant for Lundbeck and Alkermes and has been an advisor for HLS Therapeutics.