1. O9.5. NORMALIZATION OF DISTURBANCES IN PREDICTION ERROR IS RELATED TO TREATMENT RESPONSE AND RELATED TO THALAMIC GLUTAMATE LEVELS IN NON-RESPONDERS
- Author
-
Mette Odegård Nielsen, Anne Sigvard, Egill Rostrup, Birte Glenthøj, Kirsten Borup Bojesen, and Karen Tangmose
- Subjects
Normalization (statistics) ,medicine.medical_specialty ,Treatment response ,Oral Session: Digital Health/Methods ,AcademicSubjects/MED00810 ,business.industry ,Mean squared prediction error ,Glutamate receptor ,Psychiatry and Mental health ,Non responders ,O9. Oral Session: Substance Use/ Treatment ,Internal medicine ,Cardiology ,medicine ,business - Abstract
Background Prediction error is the mismatch between expected and obtained outcome, and psychosis has been linked to aberrant striatal prediction error signal. Several lines of evidence indicate alterations of the glutamatergic system to be involved in the pathophysiology of schizophrenia. We have previously reported abnormal thalamic glutamate levels at illness onset in schizophrenia patients driven by increased levels in non-responding patients, and that glutamatergic levels in the thalamus in twins dis- or concordant for psychosis were heritable and associated with the illness. Glutamatergic abnormalities may affect processing of prediction error; however, it remains unresolved if prediction error is affected by antipsychotic treatment, and to which extend treatment effect on prediction error is predicted by glutamatergic levels in patients characterized as responders or non-responders. Here, we explore treatment effects of aripiprazole on striatal prediction error signal in initially antipsychotic-naïve patients characterized as responders and non-responders and relate the findings to thalamic glutamate levels. We hypothesize a different treatment response in prediction error signal in responders and non-responders, and an association to baseline glutamate levels. Methods Thirty-three patients (age 22 ± 4 years) and 33 healthy controls (HC) matched on age and gender underwent functional Magnetic Resonance imaging (fMRI) and magnetic resonance spectroscopy (1H-MRS) (3T) at baseline and after 6 weeks of treatment with aripiprazole. Prediction error related brain activity was examined using a Monetary Incentive Delay Task. Glutamate levels were estimated in the left thalamus and analyzed using LCModel. In patients, symptom severity was assessed with the Positive and Negative Syndrome Scale. The Andreasen criteria defined responders (N=10) and non- responders (N=23). Repeated measures analysis of variance was used to test the effect of time in prediction error signal with group (responders vs non-responders vs HC) as between subject factor and time as within factor. Analysis of variance, two sample t-test and paired sample t-test evaluated group differences at baseline and follow up. In a multiple regression analyses we investigated the influence of baseline glutamate levels, symptom severity and p-aripiprazole on changes in prediction error signal in both responders and non-responders. Results Repeated measures analysis of prediction error showed an effect of group (p=0.007) and no effect of time (p=0.29) or interaction (p=0.29). The effect of group was explained by an abnormal increased prediction error signal in responders (p=0.047) and non-responders (p=0.011) compared to HC at baseline, which was normalized at follow up in responders (p=0.94) but not in non-responders (p=0.02) compared to HC. Changes in prediction error signal following treatment were predicted by glutamate levels in non-responders (p=0.03) but not in responders (p=0.85) whereas p-aripiprazole and symptom severity did not predict changes in prediction error signal (all p>0.05). Discussion The findings suggest that treatment with a partial dopamine agonist normalizes prediction error signal in patients characterized as responders. Thalamic glutamate seems to play a role in the neural coding of prediction error in patients characterized as non-responders, where increased levels of glutamate in the thalamus seems to predict a less pronounced changes in prediction error signal.
- Published
- 2020
- Full Text
- View/download PDF