O5.5. THE NEUROBIOLOGY OF NEGATIVE SYMPTOMS IN SCHIZOPHRENIA: MULTI-MODAL PET AND FMRI FINDINGS

BACKGROUND: The neurobiological mechanisms underlying anhedonia and other negative symptoms in schizophrenia are unknown. Understanding this would help identify treatments for these symptoms. Pre-clinical and human evidence shows the mu-opioid receptor plays a key role in reward processing and anhedonia. However, the contribution of Mu Opioid Receptor (MOR) signalling to negative symptoms and the reward processing abnormalities in schizophrenia is unknown. Here, we investigated for the first time in vivo in patients whether MOR availability is altered in schizophrenia and if this is associated with the neural processes underlying reward anticipation in patients with schizophrenia using multimodal neuroimaging. METHODS: Forty volunteers (n=20 patients with schizophrenia and 20 age and sex-matched healthy controls) received an [11C]-carfentanil PET scan to measure MOR availability, a structural MRI scan and a functional MRI scan while performing the Monetary Incentive Delay (MID) task to measure the neural response to reward anticipation. All the patients met criteria for persistent negative symptoms. Our primary ROI for the PET analysis was the striatum. In addition, we analysed MOR availability in brain regions in the hedonic network (the striatum, insula and anterior cingulate cortex). The fMRI analysis focused on brain regions in this hedonic network as these have previously associated with MOR mediated reward processing in humans and preclinical studies. Brain volumes of regions of interest (ROIs) were also extracted. RESULTS: The analysis showed significantly lower MOR availability in the striatum of patients with schizophrenia relative to controls (patients vs. controls (mean binding potential (BPND) ± SEM): 1.54 ± 0.06 vs. 1.7 ± 0.05, Cohen’s d= 0.7, t=-2.2, df (37), p<0.05). There was also a significant effect of both group (F (5, 222) = 334.5, p<0.05) and ROI (F (1, 222) = 5.65, p<0.05) on BPND measures in the hedonic brain network. The group* ROI interaction was not significant (F (5, 222) = 0.2167, p>0.05). There were no significant differences in the volume of the striatum or other brain regions between groups (patients vs controls: mean ± SEM (mm3) 13019 ± 302 vs 12937 ± 327 respectively, p = 0.86). Reward anticipation in controls was associated with increased neural activation in a widespread network of brain regions including the ventral striatum and insula. The activation in the ventral striatum was significantly lower in patients compared to healthy controls. MOR availability was positively correlated with neural activation in the insula during reward anticipation in controls (spearman’s rho=0.6, p=0.006) but not in patients (spearman’s rho=0.13, p=0.57). In contrast, MOR availability in the striatum was not associated with neural activation in the striatum. DISCUSSION: These data show for the first time in vivo that mu-opioid receptor availability is lower in schizophrenia across the hedonic brain network. Moreover, patients with schizophrenia show altered coupling between mu-opioid signalling in the insula and brain activation during reward anticipation. These findings identify the mu-opioid receptor as a potential therapeutic target for reward dysfunction in schizophrenia.