Abnormal cortical glutamate and GABA in individuals with depression and schizophrenia: an MRS study
Poster No:
596
Submission Type:
Abstract Submission
Authors:
Shitong Xiang1, Chao Xie1, Yijie Zhao1, Yuchao Jiang1, Chun Shen1, Yuzhu Li1, Xiao Chang1, Jianfeng Feng1
Institutions:
1Fudan University, Shanghai, Shanghai
First Author:
Co-Author(s):
Introduction:
Comorbidity in psychiatry, the co-occurrence of two or more psychiatric conditions, has received increasing attention given its high prevalence and persistence (Krueger & Eaton, 2015). Schizophrenia (SCZ) is a major psychiatric disorder and global leading cause of disability. Depressive symptoms commonly occur in schizophrenia and have a significant impact on the distress and burden of the illness (Upthegrove, Marwaha, & Birchwood, 2017). A substantial neuropharmacological evidence suggested a glutamate hypothesis for SCZ (Uno & Coyle, 2019) and a glutamate hypothesis for depression (Sanacora, Treccani, & Popoli, 2012). Our recent studies revealed a shared trajectory in the development of SCZ and depression, specifically associated with structural abnormalities in the anterior cingulate cortex (Chen et al., 2023; Jiang et al., 2023). However, there has been little analysis of underlying neurochemical mechanisms.
Methods:
Here, we utilized 7-Tesla proton magnetic resonance spectroscopy (1H-MRS) to assess the concentrations of glutamate (Glu) and γ-amino-butyric acid (GABA) in dorsal anterior cingulate cortex (dACC, Fig. 1a) of healthy participants and individuals with major depression disorder (MDD) or schizophrenia (SCZ). Briefly, participants underwent whole-brain T1-weighted MR and single-voxel proton MRS scans using a 7T Terra MRI (Siemens). LCModel (version 6.3-lL, Provencher, 1993) was used to processed the MRS data with an automated fitting routine. Individual component fitted spectra for the metabolites between 1.2 and 4.2 ppm were extracted for inspection. The concentrations of those metabolites were quantified relative to Cr+PCr (creatine plus phosphocreatine). After quality control, total 128 aged 18-55 years old participants (52 healthy controls, 40 patients with MDD and 36 patients with SCZ) were including in the following analysis. Besides sex and age, the concentration of N-acetylaspartate (NAA, a measure of neuronal integrity) and total intracranial volume were controlled as additional confounders.
·Fig.1 An illustration for the MRS data acquisition.
Results:
In the dACC, the levels of Glu and GABA were significantly lower in both MDD group and SCZ group compared to the healthy controls (for Glu, MDD vs healthy controls: t87 = -2.742, p = 0.007, Cohen's d = -0.583, SCZ vs healthy controls: t83 = -2.126, p = 0.037, Cohen's d = -0.466; for GABA, MDD vs healthy controls: t87 = -2.202, p = 0.030, Cohen's d = -0.468, SCZ vs healthy controls: t83 = -4.531, p < 0.001, Cohen's d = -0.994; Fig. 2a). Notably, there were positive relationships between Glu and GABA in the dACC among all healthy control group (r48 = 0.304, p = 0.032), MDD group (r36= 0.589, p < 0.001) and SCZ group (r32 = 0.506, p = 0.002) (Fig. 2b). Interestingly, the correlation within the patient groups showed an increasing trend, but the difference of intergroup comparisons was under the statistical significance threshold. In addition to the correlation analysis above, the comparison analysis on the ratio between Glu and GABA suggested that both patients with MDD and SCZ established a higher contrast of excitatory and inhibitory neurotransmission than that in healthy controls (MDD vs healthy controls: t87 = 2.112, p = 0.038, Cohen's d = 0.449; SCZ vs healthy controls: t83 = -3.523, p = 0.001, Cohen's d = 0.773).
·Fig.2 Abnormal cortical cneurochemical indices of the levels Glu and GABA among both patients with major depression disorder and schizophrenia.
Conclusions:
Altogether, this 7T MRS study has demonstrated that SCZ and MDD are shared common neurochemical indices in the dACC, suggestive of the deceased levels of Glu and GABA. Moreover, an altered ratio between the neurometabolites Glu and GABA in this region implicated in an abnormal excitatory/inhibitory balance, hence supporting the glutamate hypothesises of these psychiatric disorders and suggesting a converged underlying neurochemical mechanisms.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Novel Imaging Acquisition Methods:
MR Spectroscopy 2
Keywords:
GABA
Glutamate
Magnetic Resonance Spectroscopy (MRS)
Neurotransmitter
Psychiatric Disorders
Schizophrenia
Other - dACC
1|2Indicates the priority used for review
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Jiang, Y., Wang, J., Zhou, E., Palaniyappan, L., Luo, C., Ji, G., . . . Feng, J. (2023). Neuroimaging biomarkers define neurophysiological subtypes with distinct trajectories in schizophrenia. Nature Mental Health, 1(3), 186-199.
Krueger, R. F., & Eaton, N. R. (2015). Transdiagnostic factors of mental disorders. World Psychiatry Official Journal of the World Psychiatric Association, 14(1), 27-29.
Provencher, S. W. (1993). Estimation of metabolite concentrations from localized in vivo proton NMR spectra. Magn Reson Med, 30(6), 672-679.
Sanacora, G., Treccani, G., & Popoli, M. (2012). Towards a glutamate hypothesis of depression: an emerging frontier of neuropsychopharmacology for mood disorders. Neuropharmacology, 62(1), 63-77.
Uno, Y., & Coyle, J. T. (2019). Glutamate hypothesis in schizophrenia. Psychiatry Clin Neurosci, 73(5), 204-215.
Upthegrove, R., Marwaha, S., & Birchwood, M. (2017). Depression and Schizophrenia: Cause, Consequence, or Trans-diagnostic Issue? Schizophr Bull, 43(2), 240-244.