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Deficits in emotion recognition among at-risk patients may predict eventual transition to schizophrenia.
RESEARCH
The profound inability to recognize emotion in facial expression and voice tone is a hallmark of schizophrenia. Corcoran and colleagues1 found that deficits in emotion recognition may precede onset of symptoms and act as an index for identifying those most at risk.
Although criteria have been developed to identify persons at clinical high risk for schizophrenia, only about 20% to 30% of persons meeting those criteria will transition to psychosis within a 3-year period. That being the case, the researchers, whose work was supported by the National Institute of Mental Health, argued that improved prediction algorithms are needed to permit earlier intervention and prevention of this devastating neuropsychiatric disorder.
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They compared 49 patients at high risk for schizophrenia (age 12 to 30 years) with 31 healthy age- and sex-matched controls and a cohort of 93 patients with schizophrenia. A parallel study investigated normal development of face and auditory emotion recognition in 43 young persons aged 7 to 26 years.
Deficits in the at-risk patients were compared with deficits in patients with established schizophrenia and with normal neurocognitive growth curves that occur during childhood to early adulthood. High-risk status was diagnosed using the Structured Interview for Prodromal Syndromes/Scale of Prodromal Symptoms (SIPS/SOPS).
Face emotion recognition was assessed using the ER40, a tool that uses 40 color photographs to express 4 basic facial emotions (happiness, sadness, anger, fear) and a neutral composure. The ability to recognize emotional intensity was assessed using the Penn Emotion Discrimination Task, which juxtaposes 2 photos of the same face that show different intensities of the same emotion. In addition, the Wechsler Adult Intelligence Scale was used to rule out whether low IQ accounted for emotion recognition deficits. Auditory emotion recognition was assessed using 32 audio recordings of native English speakers that conveyed the same emotions as those in the ER40.
Finally, speed of cognitive processing and attention/vigilance was assessed in the developmental cohort via the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery, which was also administered to the clinical high-risk group.
Emotional recognition deficits predict schizophrenia
Within 2.5 years, schizophrenia developed in 7 (14%) of the high-risk patients. Deficits in emotion recognition among the high-risk patients were strongly correlated with eventual transition to schizophrenia. In fact, the most sensitive classification model for schizophrenia onset was face emotion processing and negative symptoms, with an accuracy rate of 96%. General neurocognitive measures, such as attention vigilance and processing speed, were nonpredictive.
Whereas no differences were seen in ER40 and Penn Emotion Discrimination Task scores between healthy controls and high-risk patients who did not transition to schizophrenia, significant differences (P ≤ .001) were seen between high-risk patients who did transition and the other participants.
The ripening of emotional intelligence
In the parallel developmental study, face emotion recognition abilities were found to reach maturity by age 14 while auditory emotion recognition emerged before age 14 and continued to develop into adulthood. Development of speed of processing and attention/vigilance generally did not begin until after age 14 years.
Mean scores for face emotion recognition among high-risk patients who transitioned to schizophrenia and patients with established schizophrenia were at or below those observed in persons aged 10 years. High-risk patients who did not transition to schizophrenia and healthy controls, however, demonstrated age-appropriate performance.
The researchers concluded that profound and identifiable deficits in emotion recognition exist before onset of psychotic symptoms in high-risk patients who transition to schizophrenia. Screening for these deficits may identify those at greatest risk and set the stage for early remediation.