Cerebral Glutamate and Gamma-Aminobutyric Acid Levels in Individuals at Ultra-high Risk for Psychosis and the Association With Clinical Symptoms and Cognition

Background Studies examining glutamate or gamma-aminobutyric acid (GABA) in ultra-high risk for psychosis (UHR) and the association with pathophysiology and cognition have shown conflicting results. We aimed to determine whether perturbed glutamate and GABA levels in the anterior cingulate cortex and glutamate levels in the left thalamus were present in UHR individuals and to investigate associations between metabolite levels and clinical symptoms and cognition. Methods We included 122 UHR individuals and 60 healthy control subjects. Participants underwent proton magnetic resonance spectroscopy to estimate glutamate and GABA levels and undertook clinical and cognitive assessments. Results We found no differences in metabolite levels between UHR individuals and healthy control subjects. In UHR individuals, we found negative correlations in the anterior cingulate cortex between the composite of glutamate and glutamine (Glx) and the Comprehensive Assessment of At-Risk Mental States composite score (p = .04) and between GABA and alogia (p = .01); positive associations in the anterior cingulate cortex between glutamate (p = .01) and Glx (p = .01) and spatial working memory and between glutamate (p = .04), Glx (p = .04), and GABA (p = .02) and set-shifting; and a positive association in the thalamus between glutamate and attention (p = .04). No associations between metabolites and clinical or cognitive scores were found in the healthy control subjects. Conclusions An association between glutamate and GABA levels and clinical symptoms and cognition found only in UHR individuals suggests a loss of the normal relationship between metabolite levels and cognitive function. Longitudinal studies with investigation of clinical and cognitive outcome and the association with baseline levels of glutamate and GABA could illuminate whether glutamatergic and GABAergic dysfunction predicts clinical outcome.