Glutamine and GABA alterations in cingulate cortex may underlie alcohol drinking in a rat model of co-occurring alcohol use disorder and schizophrenia: an 1H-MRS study

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Abstract

Alcohol use disorder commonly occurs in patients with schizophrenia and significantly worsens the clinical course of the disorder. The neurobiological underpinnings of alcohol drinking are not well understood. Magnetic resonance spectroscopy (MRS) has been used to assess the neurochemical substrates that may be associated with alcohol drinking in patients; however, the causal impact of these findings remains elusive, highlighting the need for studies in animal models. This study performed MRS in the neonatal ventral hippocampal lesioned (NVHL) rat model, a model of co-occurring schizophrenia and substance use disorders. NVHL lesions (or sham surgeries) were performed on post-natal day 7 and animals were given brief exposure to alcohol during adolescence (10% v/v in a 2-bottle choice design). Animals were re-exposed to alcohol during adulthood (20% v/v) until a stable drinking baseline was established, and then forced into abstinence to control for the effects of differential alcohol drinking. Animals were scanned for MRS after one month of abstinence. NVHL rats consumed significantly more alcohol than sham rats and in the cingulate cortex showed significantly higher levels of GABA and glutamine. Significantly lower GABA levels were observed in the nucleus accumbens. No differences between the NVHL and sham animals were observed in the hippocampus. Correlation analysis revealed that GABA and glutamine concentrations in the cingulate cortex significantly correlated with the rats’ alcohol drinking prior to 30 days of forced abstinence. These findings suggest that a potential dysfunction in the glutamate/GABA–glutamine cycle may contribute to alcohol drinking in a rat model of schizophrenia, and this dysfunction could be targeted in future treatment-focused studies.

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The LCModel method analyzes an in vivo spectrum as a Linear Combination of Model spectra of metabolite solutions in vitro. By using complete model spectra, rather than just individual resonances, maximum information and uniqueness are incorporated into the analysis. A constrained regularization method accounts for differences in phase, baseline, and lineshapes between the in vitro and in vivo spectra, and estimates the metabolite concentrations and their uncertainties. LCModel is fully automatic in that the only input is the time-domain in vivo data. The lack of subjective interaction should help the exchange and comparison of results. More than 3000 human brain STEAM spectra from patients and healthy volunteers have been analyzed with LCModel. N-acetylaspartate, cholines, creatines, myo-inositol, and glutamate can be reliably determined, and abnormal levels of these or elevated levels of lactate, alanine, scyllo-inositol, glutamine, or glucose clearly indicate numerous pathologies. A computer program will be available.

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Ryne C. Ramaker, Kevin M. Bowling, Brittany N Lasseigne … (2017)

Background Psychiatric disorders are multigenic diseases with complex etiology that contribute significantly to human morbidity and mortality. Although clinically distinct, several disorders share many symptoms, suggesting common underlying molecular changes exist that may implicate important regulators of pathogenesis and provide new therapeutic targets. Methods We performed RNA sequencing on tissue from the anterior cingulate cortex, dorsolateral prefrontal cortex, and nucleus accumbens from three groups of 24 patients each diagnosed with schizophrenia, bipolar disorder, or major depressive disorder, and from 24 control subjects. We identified differentially expressed genes and validated the results in an independent cohort. Anterior cingulate cortex samples were also subjected to metabolomic analysis. ChIP-seq data were used to characterize binding of the transcription factor EGR1. Results We compared molecular signatures across the three brain regions and disorders in the transcriptomes of post-mortem human brain samples. The most significant disease-related differences were in the anterior cingulate cortex of schizophrenia samples compared to controls. Transcriptional changes were assessed in an independent cohort, revealing the transcription factor EGR1 as significantly down-regulated in both cohorts and as a potential regulator of broader transcription changes observed in schizophrenia patients. Additionally, broad down-regulation of genes specific to neurons and concordant up-regulation of genes specific to astrocytes was observed in schizophrenia and bipolar disorder patients relative to controls. Metabolomic profiling identified disruption of GABA levels in schizophrenia patients. Conclusions We provide a comprehensive post-mortem transcriptome profile of three psychiatric disorders across three brain regions. We highlight a high-confidence set of independently validated genes differentially expressed between schizophrenia and control patients in the anterior cingulate cortex and integrate transcriptional changes with untargeted metabolite profiling. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0458-5) contains supplementary material, which is available to authorized users.

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Author and article information

Contributors

Jibran Y. Khokhar: jkhokha@uwo.ca

Journal

Journal ID (nlm-ta): Schizophrenia (Heidelb)

Journal ID (iso-abbrev): Schizophrenia (Heidelb)

Title: Schizophrenia

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2754-6993

Publication date (Electronic): 23 August 2022

Publication date PMC-release: 23 August 2022

Publication date Collection: 2022

Volume: 8

Issue: 1

Electronic Location Identifier: 67

Affiliations

[1 ]GRID grid.39381.30, ISNI 0000 0004 1936 8884, Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, , University of Western Ontario, ; London, ON Canada

[2 ]GRID grid.254880.3, ISNI 0000 0001 2179 2404, Department of Radiology, Biomedical NMR Research Center, , Geisel School of Medicine at Dartmouth, ; Lebanon, NH USA

[3 ]GRID grid.240206.2, ISNI 0000 0000 8795 072X, Psychotic Disorders Division, , McLean Hospital, ; Belmont, MA USA

[4 ]GRID grid.38142.3c, ISNI 000000041936754X, Department of Psychiatry, , Harvard Medical School, ; Boston, MA USA

[5 ]GRID grid.254880.3, ISNI 0000 0001 2179 2404, Department of Psychiatry, , Geisel School of Medicine at Dartmouth, ; Lebanon, NH USA

Article

Publisher ID: 272

DOI: 10.1038/s41537-022-00272-6

PMC ID: 9399110

PubMed ID: 35999232

SO-VID: bd677ae3-e749-4194-b291-66e60c5bf9fa

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 21 January 2022

Date accepted : 1 August 2022

Funding

Funded by: FundRef https://doi.org/10.13039/501100000024, Gouvernement du Canada | Canadian Institutes of Health Research (Instituts de Recherche en Santé du Canada);

Award ID: PJT-173442

Award Recipient : Jibran Y. Khokhar