Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity.
Treatment for major depressive disorder (depression) often has partial efficacy and a large portion of patients are treatment resistant. Recent studies implicate reduced somatostatin (SST) interneuron inhibition in depression, and new pharmacology boosting this inhibition via positive allosteric mod...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2024-12-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1012693 |
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| author | Alexandre Guet-McCreight Frank Mazza Thomas D Prevot Etienne Sibille Etay Hay |
| author_facet | Alexandre Guet-McCreight Frank Mazza Thomas D Prevot Etienne Sibille Etay Hay |
| author_sort | Alexandre Guet-McCreight |
| collection | DOAJ |
| description | Treatment for major depressive disorder (depression) often has partial efficacy and a large portion of patients are treatment resistant. Recent studies implicate reduced somatostatin (SST) interneuron inhibition in depression, and new pharmacology boosting this inhibition via positive allosteric modulators of α5-GABAA receptors (α5-PAM) offers a promising effective treatment. However, testing the effect of α5-PAM on human brain activity is limited, meriting the use of detailed simulations. We utilized our previous detailed computational models of human depression microcircuits with reduced SST interneuron inhibition and α5-PAM effects, to simulate EEG of individual microcircuits across depression severity and α5-PAM doses. We developed machine learning models that predicted optimal dose from EEG with high accuracy and recovered microcircuit activity and EEG. This study provides dose prediction models for α5-PAM administration based on EEG biomarkers of depression severity. Given limitations in doing the above in the living human brain, the results and tools we developed will facilitate translation of α5-PAM treatment to clinical use. |
| format | Article |
| id | doaj-art-c8b1dada79f842db847d5e09cd0df684 |
| institution | DOAJ |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-c8b1dada79f842db847d5e09cd0df6842025-08-20T02:45:06ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582024-12-012012e101269310.1371/journal.pcbi.1012693Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity.Alexandre Guet-McCreightFrank MazzaThomas D PrevotEtienne SibilleEtay HayTreatment for major depressive disorder (depression) often has partial efficacy and a large portion of patients are treatment resistant. Recent studies implicate reduced somatostatin (SST) interneuron inhibition in depression, and new pharmacology boosting this inhibition via positive allosteric modulators of α5-GABAA receptors (α5-PAM) offers a promising effective treatment. However, testing the effect of α5-PAM on human brain activity is limited, meriting the use of detailed simulations. We utilized our previous detailed computational models of human depression microcircuits with reduced SST interneuron inhibition and α5-PAM effects, to simulate EEG of individual microcircuits across depression severity and α5-PAM doses. We developed machine learning models that predicted optimal dose from EEG with high accuracy and recovered microcircuit activity and EEG. This study provides dose prediction models for α5-PAM administration based on EEG biomarkers of depression severity. Given limitations in doing the above in the living human brain, the results and tools we developed will facilitate translation of α5-PAM treatment to clinical use.https://doi.org/10.1371/journal.pcbi.1012693 |
| spellingShingle | Alexandre Guet-McCreight Frank Mazza Thomas D Prevot Etienne Sibille Etay Hay Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity. PLoS Computational Biology |
| title | Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity. |
| title_full | Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity. |
| title_fullStr | Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity. |
| title_full_unstemmed | Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity. |
| title_short | Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity. |
| title_sort | therapeutic dose prediction of α5 gaba receptor modulation from simulated eeg of depression severity |
| url | https://doi.org/10.1371/journal.pcbi.1012693 |
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