MPFC Metabolites and Their Association with Resting-State EEG in Schizophrenia Spectrum Disorder

Poster No:

683 

Submission Type:

Abstract Submission 

Authors:

Genc Hasanaj1, Berkhan Karsli2, Verena Meisinger3, Marcel Kallweit4, Gizem Vural5, Lukas Röll4, Julian Melcher6, Boris Papazov7, Joanna Moussiopoulou8, Vladislav Yakimov4, Elias Wagner4, Florian Raabe9, Daniel Keeser10

Institutions:

1Ludwig Maximillian University, Munich, Germany, 2Ludwig Maximilian University, Munich, Bavaria, 3Ludwig Maximilian University, Munich, Germany, 4LMU University Hospital, Munich, Germany, 5LMU Klinikum, Munich, Other, 6LMU Klinikum, Munich, Bavaria, 7LMU Munich, München, Bayern, 8LMU Klinikum, München, Germany, 9Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany, 10Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany

First Author:

Genc Hasanaj  
Ludwig Maximillian University
Munich, Germany

Co-Author(s):

Berkhan Karsli  
Ludwig Maximilian University
Munich, Bavaria
Verena Meisinger  
Ludwig Maximilian University
Munich, Germany
Marcel Kallweit  
LMU University Hospital
Munich, Germany
Gizem Vural  
LMU Klinikum
Munich, Other
Lukas Röll  
LMU University Hospital
Munich, Germany
Julian Melcher  
LMU Klinikum
Munich, Bavaria
Boris Papazov  
LMU Munich
München, Bayern
Joanna Moussiopoulou  
LMU Klinikum
München, Germany
Vladislav Yakimov  
LMU University Hospital
Munich, Germany
Elias Wagner  
LMU University Hospital
Munich, Germany
Florian Raabe  
Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University
Munich, Germany
Daniel Keeser  
Department of Psychiatry and Psychotherapy, University Hospital LMU
Munich, Germany

Introduction:

Aberrant modulatory effects and concentration of metabolites in the Medial Prefrontal Cortex (mPFC) have been the focus of recent research (Dixon et al., 2022), especially in the context of schizophrenia spectrum disorders (SSD). To date, evidence for the modulatory role of metabolites on directly measured neuronal mass activity in the brain is lacking. In this study, we investigated the possible role of gamma-aminobutyric acid (GABA) and Glutamine+Glutamate (Glx) in modulating resting-state EEG (rsEEG) activity for both healthy controls (HC) and patients with SSD. With this study, we aim to investigate the direct relationship between metabolite activity and rsEEG oscillations in sensor and source space to gain more mechanistic insights between these modalities and thus provide a basis for clinical translation.

Methods:

Data from 63 patients with SSD and 62 HC was collected at the University Hospital LMU . Participants underwent multimodal MRI using a 3T MRI scanner, focusing on Single Voxel Spectroscopy at the mPFC (voxel size 20x20x20 mm3). Osprey and LC-Model were used to process the MRS data. Exclusions based on Cramer-Rao lower bounds (>50% SD), and later removal of outliers (2.5 SD above and below the median), the further analysis included 44 SSDs and 52 HCs. The rsEEG was recorded with 32 electrodes according to the international 10/20 system and included 5 minutes each with eyes open (EO) and eyes closed (EC). Data were preprocessed within an ICA preprocessing pipeline adapted and customized from (Adams et al., 2022). The source localized EEG activity of the mPFC ROI was extracted and the Power Spectrum Density was calculated within this source localized activity. Multiple linear regression using patient group as a covariate and Pearson correlation techniques were applied to estimate oscillatory activity from metabolites.

Results:

Comparison between SSD and HC group showed no significant difference in metabolite concentration (Glx, GABA; p > .05). For the EC condition, the interaction of Glx and Group was significantly associated with Theta (β = 0.0012, t = 3.07, p = 0.003), Beta (β = 0.0009, t = 1.99, p = 0.050), and Total Absolute Power (β = 0.0037, t = 2.22, p = 0.029). Specifically, Glx correlated with Theta (r = 0.51, p < 0.001), Beta (r = 0.43, p = 0.004), and Total Absolute Power (r = 0.45, p = 0.002) in the SSD group, but no correlation was found for the HC group. For the EO condition, the Glx and Group interaction significantly predicted Theta (β = 0.0007, t = 2.41, p = 0.018). As with the EC condition, Glx correlated significantly with Theta activity in the SSD (r = 0.47, p = 0.001) but not in the HC group.

Conclusions:

This study shows a distinct pattern of association between metabolite levels and canonical frequency band powers in the different resting states of the patient group. The interaction of Glx and Group was significantly associated with Theta, Beta, and Total Absolute Power during the EC condition. Additionally, Glx correlated with these power values, while no such correlation was found in the HC group. Similarly, for the EO condition, the interaction of Glx and Group was also significantly associated with Theta activity, with a correlation observed in the SSD but not in the HC group. The results suggest differences in the relationship between glutamatergic activity and brain oscillations between the SSD and HC groups, particularly in the EC and EO conditions. There are contradictory results in the literature regarding the differences in metabolite levels in different patient groups and under different conditions (Dixon et al., 2022). The absence of significant group difference could be the possible normalization effect of antipsychotic medication in the SSD group (Kegeles et al., 2012). Due to the heterogeneity within the SSD group and the lack of concurrent MRS and EEG acquisition, which may introduce variability (Al-Iedani et al., 2018) and affect generalizability, these results must be interpreted with caution.

Disorders of the Nervous System:

Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1

Modeling and Analysis Methods:

EEG/MEG Modeling and Analysis 2

Novel Imaging Acquisition Methods:

MR Spectroscopy

Physiology, Metabolism and Neurotransmission :

Neurophysiology of Imaging Signals
Physiology, Metabolism and Neurotransmission Other

Keywords:

DISORDERS
Electroencephaolography (EEG)
GABA
Glutamate
Magnetic Resonance Spectroscopy (MRS)
Psychiatric Disorders
Schizophrenia
Source Localization

1|2Indicates the priority used for review

Provide references using author date format

Adams, R. A. (2022). Computational Modeling of Electroencephalography and Functional Magnetic Resonance Imaging Paradigms Indicates a Consistent Loss of Pyramidal Cell Synaptic Gain in Schizophrenia. Biological Psychiatry, 91(2), 202–215.

Al-Iedani (2018). Diurnal stability and long-term repeatability of neurometabolites using single voxel 1H magnetic resonance spectroscopy. European Journal of Radiology, 108, 107–113.

Dixon, (2022). Frontal neural metabolite changes in schizophrenia and their association with cognitive control: A systematic review. Neuroscience and Biobehavioral Reviews, 132, 224–247.

Kegeles, (2012). Elevated prefrontal cortex γ-aminobutyric acid and glutamate-glutamine levels in schizophrenia measured in vivo with proton magnetic resonance spectroscopy. Archives of General Psychiatry, 69(5), 449.