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Dopamine Synthesis Capacity and GABA and Glutamate Levels Separate Antipsychotic-Naïve Patients With First-Episode Psychosis From Healthy Control Subjects in a Multimodal Prediction Model
BACKGROUND: Disturbances in presynaptic dopamine activity and levels of GABA (gamma-aminobutyric acid) and glutamate plus glutamine collectively may have a role in the pathophysiology of psychosis, although separately they are poor diagnostic markers. We tested whether these neurotransmitters in com...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382695/ https://www.ncbi.nlm.nih.gov/pubmed/37519478 http://dx.doi.org/10.1016/j.bpsgos.2022.05.004 |
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author | Sigvard, Anne K. Bojesen, Kirsten Borup Ambrosen, Karen S. Nielsen, Mette Ødegaard Gjedde, Albert Tangmose, Karen Kumakura, Yoshitaka Edden, Richard Fuglø, Dan Jensen, Lars Thorbjørn Rostrup, Egill Ebdrup, Bjørn H. Glenthøj, Birte Yding |
author_facet | Sigvard, Anne K. Bojesen, Kirsten Borup Ambrosen, Karen S. Nielsen, Mette Ødegaard Gjedde, Albert Tangmose, Karen Kumakura, Yoshitaka Edden, Richard Fuglø, Dan Jensen, Lars Thorbjørn Rostrup, Egill Ebdrup, Bjørn H. Glenthøj, Birte Yding |
author_sort | Sigvard, Anne K. |
collection | PubMed |
description | BACKGROUND: Disturbances in presynaptic dopamine activity and levels of GABA (gamma-aminobutyric acid) and glutamate plus glutamine collectively may have a role in the pathophysiology of psychosis, although separately they are poor diagnostic markers. We tested whether these neurotransmitters in combination improve the distinction of antipsychotic-naïve patients with first-episode psychosis from healthy control subjects. METHODS: We included 23 patients (mean age 22.3 years, 9 male) and 20 control subjects (mean age 22.4 years, 8 male). We determined dopamine metabolism in the nucleus accumbens and striatum from (18)F-fluorodopa ((18)F-FDOPA) positron emission tomography. We measured GABA levels in the anterior cingulate cortex (ACC) and glutamate plus glutamine levels in the ACC and left thalamus with 3T proton magnetic resonance spectroscopy. We used binominal logistic regression for unimodal prediction when we modeled neurotransmitters individually and for multimodal prediction when we combined the 3 neurotransmitters. We selected the best combination based on Akaike information criterion. RESULTS: Individual neurotransmitters failed to predict group. Three triple neurotransmitter combinations significantly predicted group after Benjamini-Hochberg correction. The best model (Akaike information criterion 48.5) carried 93.5% of the cumulative model weight. It reached a classification accuracy of 83.7% (p = .003) and included dopamine synthesis capacity (K(i)(4p)) in the nucleus accumbens (p = .664), GABA levels in the ACC (p = .019), glutamate plus glutamine levels in the thalamus (p = .678), and the interaction term K(i)(4p) × GABA (p = .016). CONCLUSIONS: Our multimodal approach proved superior classification accuracy, implying that the pathophysiology of patients represents a combination of neurotransmitter disturbances rather than aberrations in a single neurotransmitter. Particularly aberrant interrelations between K(i)(4p) in the nucleus accumbens and GABA values in the ACC appeared to contribute diagnostic information. |
format | Online Article Text |
id | pubmed-10382695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103826952023-07-30 Dopamine Synthesis Capacity and GABA and Glutamate Levels Separate Antipsychotic-Naïve Patients With First-Episode Psychosis From Healthy Control Subjects in a Multimodal Prediction Model Sigvard, Anne K. Bojesen, Kirsten Borup Ambrosen, Karen S. Nielsen, Mette Ødegaard Gjedde, Albert Tangmose, Karen Kumakura, Yoshitaka Edden, Richard Fuglø, Dan Jensen, Lars Thorbjørn Rostrup, Egill Ebdrup, Bjørn H. Glenthøj, Birte Yding Biol Psychiatry Glob Open Sci Archival Report BACKGROUND: Disturbances in presynaptic dopamine activity and levels of GABA (gamma-aminobutyric acid) and glutamate plus glutamine collectively may have a role in the pathophysiology of psychosis, although separately they are poor diagnostic markers. We tested whether these neurotransmitters in combination improve the distinction of antipsychotic-naïve patients with first-episode psychosis from healthy control subjects. METHODS: We included 23 patients (mean age 22.3 years, 9 male) and 20 control subjects (mean age 22.4 years, 8 male). We determined dopamine metabolism in the nucleus accumbens and striatum from (18)F-fluorodopa ((18)F-FDOPA) positron emission tomography. We measured GABA levels in the anterior cingulate cortex (ACC) and glutamate plus glutamine levels in the ACC and left thalamus with 3T proton magnetic resonance spectroscopy. We used binominal logistic regression for unimodal prediction when we modeled neurotransmitters individually and for multimodal prediction when we combined the 3 neurotransmitters. We selected the best combination based on Akaike information criterion. RESULTS: Individual neurotransmitters failed to predict group. Three triple neurotransmitter combinations significantly predicted group after Benjamini-Hochberg correction. The best model (Akaike information criterion 48.5) carried 93.5% of the cumulative model weight. It reached a classification accuracy of 83.7% (p = .003) and included dopamine synthesis capacity (K(i)(4p)) in the nucleus accumbens (p = .664), GABA levels in the ACC (p = .019), glutamate plus glutamine levels in the thalamus (p = .678), and the interaction term K(i)(4p) × GABA (p = .016). CONCLUSIONS: Our multimodal approach proved superior classification accuracy, implying that the pathophysiology of patients represents a combination of neurotransmitter disturbances rather than aberrations in a single neurotransmitter. Particularly aberrant interrelations between K(i)(4p) in the nucleus accumbens and GABA values in the ACC appeared to contribute diagnostic information. Elsevier 2022-05-30 /pmc/articles/PMC10382695/ /pubmed/37519478 http://dx.doi.org/10.1016/j.bpsgos.2022.05.004 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Archival Report Sigvard, Anne K. Bojesen, Kirsten Borup Ambrosen, Karen S. Nielsen, Mette Ødegaard Gjedde, Albert Tangmose, Karen Kumakura, Yoshitaka Edden, Richard Fuglø, Dan Jensen, Lars Thorbjørn Rostrup, Egill Ebdrup, Bjørn H. Glenthøj, Birte Yding Dopamine Synthesis Capacity and GABA and Glutamate Levels Separate Antipsychotic-Naïve Patients With First-Episode Psychosis From Healthy Control Subjects in a Multimodal Prediction Model |
title | Dopamine Synthesis Capacity and GABA and Glutamate Levels Separate Antipsychotic-Naïve Patients With First-Episode Psychosis From Healthy Control Subjects in a Multimodal Prediction Model |
title_full | Dopamine Synthesis Capacity and GABA and Glutamate Levels Separate Antipsychotic-Naïve Patients With First-Episode Psychosis From Healthy Control Subjects in a Multimodal Prediction Model |
title_fullStr | Dopamine Synthesis Capacity and GABA and Glutamate Levels Separate Antipsychotic-Naïve Patients With First-Episode Psychosis From Healthy Control Subjects in a Multimodal Prediction Model |
title_full_unstemmed | Dopamine Synthesis Capacity and GABA and Glutamate Levels Separate Antipsychotic-Naïve Patients With First-Episode Psychosis From Healthy Control Subjects in a Multimodal Prediction Model |
title_short | Dopamine Synthesis Capacity and GABA and Glutamate Levels Separate Antipsychotic-Naïve Patients With First-Episode Psychosis From Healthy Control Subjects in a Multimodal Prediction Model |
title_sort | dopamine synthesis capacity and gaba and glutamate levels separate antipsychotic-naïve patients with first-episode psychosis from healthy control subjects in a multimodal prediction model |
topic | Archival Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382695/ https://www.ncbi.nlm.nih.gov/pubmed/37519478 http://dx.doi.org/10.1016/j.bpsgos.2022.05.004 |
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